From 856ff88440c039c80c9250cdd9fdfedef80136e8 Mon Sep 17 00:00:00 2001 From: Pine Date: Mon, 17 Aug 2026 21:25:46 +0800 Subject: [PATCH] =?UTF-8?q?feat:=20=E6=8B=86=E5=87=BA=20FastAPI=20?= =?UTF-8?q?=E7=8B=AC=E7=AB=8B=E5=90=8E=E7=AB=AF=20+=20MQTT=20=E6=8E=A7?= =?UTF-8?q?=E5=88=B6=20+=20=E9=98=BF=E9=87=8C=E4=BA=91=20AI?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 后端（backend/，FastAPI :10085）： - 全部数据 REST 接口：dashboard 快照 / 企业分区 / 播放列表 / 媒体 / 设置 - MQTT 控制通道：opc/display/command（切页/播放/卡片/通知）， 管理端 POST /api/display/command → MQTT 广播 → 所有大屏同步响应 - 阿里云 DashScope：通义千问 LLM + 函数调用（工具经 MQTT 广播）， paraformer-realtime-v2 语音识别 /api/ai/asr - 媒体资源统一由后端存储返回（上传/列表/静态服务） - SSE /api/events 保留作 MQTT 不可用时的兼容回退 前端： - config.js + .env.local 配置后端地址与 MQTT 账号（前端 dpm / 服务端 dpmserver） - mqtt.js 客户端 + useMqttControl（MQTT 驱动切页/媒体/卡片/通知） - DpmOverlays 全局覆盖层（通知 toast + 企业/分区/总览卡片） - useParkSim 改为后端 API 数据源（离线回退本地模拟） - AiChatPanel：对话走后端 LLM（工具调用），语音走本地录音 + 后端 ASR - MediaScreen：媒体控制走 MQTT（保留 SSE 回退），修复 useEffect TDZ Rust：lib.rs 移除内嵌 HTTP 服务器，只保留薄壳（窗口/权限/自启/npc 隧道） 安全：backend/.env、.env.local、media、data.json 已 gitignore --- .gitignore | 13 + backend/.env.example | 22 + backend/.python-version | 1 + backend/README.md | 87 ++++ backend/app/__init__.py | 0 backend/app/ai_tools.py | 174 ++++++++ backend/app/asr.py | 93 +++++ backend/app/config.py | 69 ++++ backend/app/event_bus.py | 44 ++ backend/app/llm.py | 197 +++++++++ backend/app/main.py | 94 +++++ backend/app/mqtt.py | 105 +++++ backend/app/routers.py | 383 ++++++++++++++++++ backend/app/sim_engine.py | 156 ++++++++ backend/app/storage.py | 106 +++++ backend/main.py | 8 + backend/pyproject.toml | 14 + backend/uv.lock | 579 +++++++++++++++++++++++++++ package-lock.json | 422 ++++++++++++++++++- package.json | 1 + src-tauri/src/lib.rs | 29 +- src/components/AiChatPanel.jsx | 374 ++++++++--------- src/components/DpmOverlays.jsx | 160 ++++++++ src/components/ParkOverviewStrip.jsx | 5 +- src/components/ScreenLayout.jsx | 9 +- src/config.js | 19 + src/pages/DataScreen.jsx | 123 +----- src/pages/MediaScreen.jsx | 41 ++ src/styles/datascreen.css | 189 +++++++++ src/utils/api.js | 15 +- src/utils/mqtt.js | 82 ++++ src/utils/parkData.js | 23 +- src/utils/useMqttControl.js | 95 +++++ yarn.lock | 285 ++++++++++++- 34 files changed, 3639 insertions(+), 378 deletions(-) create mode 100644 backend/.env.example create mode 100644 backend/.python-version create mode 100644 backend/README.md create mode 100644 backend/app/__init__.py create mode 100644 backend/app/ai_tools.py create mode 100644 backend/app/asr.py create mode 100644 backend/app/config.py create mode 100644 backend/app/event_bus.py create mode 100644 backend/app/llm.py create mode 100644 backend/app/main.py create mode 100644 backend/app/mqtt.py create mode 100644 backend/app/routers.py create mode 100644 backend/app/sim_engine.py create mode 100644 backend/app/storage.py create mode 100644 backend/main.py create mode 100644 backend/pyproject.toml create mode 100644 backend/uv.lock create mode 100644 src/components/DpmOverlays.jsx create mode 100644 src/config.js create mode 100644 src/utils/mqtt.js create mode 100644 src/utils/useMqttControl.js diff --git a/.gitignore b/.gitignore index 88dd7a6..4d1b13e 100644 --- a/.gitignore +++ b/.gitignore @@ -12,6 +12,14 @@ dist dist-ssr *.local +# 后端密钥 / 前端本地配置（含阿里云密钥、MQTT 凭据，不入库） +backend/.env +.env.local + +# 后端运行时数据（媒体上传、持久化配置） +backend/media/ +backend/data.json + # Editor directories and files .vscode/* !.vscode/extensions.json @@ -25,3 +33,8 @@ dist-ssr # 本地数据资料（不入库） 数据资料/ + +# Python +.venv/ +__pycache__/ +*.pyc diff --git a/backend/.env.example b/backend/.env.example new file mode 100644 index 0000000..fa775c9 --- /dev/null +++ b/backend/.env.example @@ -0,0 +1,22 @@ +# OPC 智能园区后端环境配置（复制为 .env 或直接 export） +# 注意：backend/.env 已 gitignore，含阿里云密钥与 MQTT 凭据，勿提交 + +# HTTP 监听（也可用 FASTAPI_HOST/FASTAPI_PORT） +DPM_HOST=0.0.0.0 +DPM_PORT=10085 + +# MQTT Broker（局域网 EMQX） +DPM_MQTT_ENABLED=1 +DPM_MQTT_HOST=192.168.1.3 +DPM_MQTT_PORT=1883 +# 服务端发布账号（在 EMQX 认证中创建） +DPM_MQTT_USERNAME=dpmserver +DPM_MQTT_PASSWORD=123456 +# 前端 WebSocket 接入地址（前端在项目根 .env.local 配置，账号 dpm） +DPM_MQTT_WS=ws://192.168.1.3:8083/mqtt +DPM_MQTT_TICK_INTERVAL=2.2 + +# 阿里云 DashScope（LLM + 语音识别） +DASHSCOPE_API_KEY=sk-xxx +DPM_LLM_MODEL=qwen-plus +DPM_ASR_MODEL=paraformer-realtime-v2 diff --git a/backend/.python-version b/backend/.python-version new file mode 100644 index 0000000..e4fba21 --- /dev/null +++ b/backend/.python-version @@ -0,0 +1 @@ +3.12 diff --git a/backend/README.md b/backend/README.md new file mode 100644 index 0000000..525ce1c --- /dev/null +++ b/backend/README.md @@ -0,0 +1,87 @@ +# OPC 智能园区后端（FastAPI + MQTT） + +独立后端服务：**所有数据通过 REST API 提供**，**页面/媒体控制通过 MQTT 下发**，媒体资源由后端统一存储与返回。 + +## 架构 + +``` +┌──────────────┐ REST（全部数据/媒体/设置） ┌────────────────┐ +│ Tauri 大屏 │ ◄────────────────────────── │ FastAPI :10085 │ +│ (React 前端) │ └───────┬────────┘ +│ │ MQTT 订阅 opc/display/command │ MQTT 发布 +│ 账号: dpm │ ◄────────────────────────────────────│ 账号: dpmserver +└──────┬───────┘ MQTT Broker (EMQX) │ + │ 192.168.1.3:1883 │ + └───────────────────────────────────────────────┘ +``` + +- **数据**：`GET /api/dashboard/snapshot`（每 2.2s 刷新，模拟引擎在后端运行）等 +- **控制**：`POST /api/display/command` → MQTT `opc/display/command` → 所有大屏订阅同步响应 +- **媒体**：上传/列表/播放列表/`/file` 静态返回（图片/视频统一由后端托管） +- **AI**：通义千问（DashScope）+ 工具调用（切页/控制/卡片/通知，经 MQTT 广播）；语音识别用阿里云 paraformer + +## 启动 + +```bash +cd backend +python3 -m venv .venv +.venv/bin/pip install -r requirements.txt +cp .env.example .env # 按需修改（含 DashScope Key、MQTT 账号） +.venv/bin/python main.py +``` + +启动后：API 与前端页面均在 `http://0.0.0.0:10085`（浏览器直接打开即大屏）。 + +## 环境变量（backend/.env） + +| 变量 | 说明 | +|---|---| +| `DPM_HOST` / `DPM_PORT`（或 `FASTAPI_HOST`/`FASTAPI_PORT`） | 监听地址，默认 `0.0.0.0:10085` | +| `DPM_MQTT_HOST` / `DPM_MQTT_PORT` | MQTT broker 地址，默认读 `MQTT_BROKER_HOST/PORT` | +| `MQTT_USERNAME` / `MQTT_PASSWORD` | **服务端发布账号：dpmserver / 123456** | +| `DASHSCOPE_API_KEY` | 阿里云 DashScope（LLM + 语音识别） | +| `DPM_LLM_MODEL` | 默认 `qwen-plus` | +| `DPM_ASR_MODEL` | 默认 `paraformer-realtime-v2` | + +> 前端连接配置在项目根 `.env.local`（已 gitignore）：`VITE_API_BASE`、`VITE_MQTT_URL`、`VITE_MQTT_USERNAME=dpm`、`VITE_MQTT_PASSWORD=123456`。 + +## MQTT 主题 + +| 主题 | 方向 | 说明 | +|---|---|---| +| `opc/display/command` | 后端→前端 | `{cmd_id, ts, action, params}`，action: `navigate` / `navigate_rel` / `play` / `pause` / `next` / `prev` / `alert` / `show_card` / `set_mode` | +| `opc/dashboard/tick` | 后端→前端 | 数据快照（`{ts, snapshot}`） | +| `opc/display/ack` | 前端→后端 | 指令回执（预留） | + +## 控制示例 + +```bash +# 切换页面（数据大屏 / 数字孪生 / AI 助手 / 媒体轮播） +curl -X POST http://localhost:10085/api/display/command \ + -H "Content-Type: application/json" \ + -d '{"action":"navigate","params":{"page":"/twin"}}' + +# 媒体控制 +curl -X POST http://localhost:10085/api/display/command \ + -d '{"action":"next","params":{}}' + +# 大屏通知 +curl -X POST http://localhost:10085/api/display/command \ + -d '{"action":"alert","params":{"title":"园区通知","content":"..."}}' +``` + +## 关键接口 + +- `GET /api/dashboard/snapshot` — 大屏全量数据快照 +- `GET /api/park/companies` · `GET /api/park/zones` — 企业分布 +- `POST /api/ai/chat` — AI 对话（`{messages:[{role,content}]}` → `{reply, tools, mqtt_published}`） +- `POST /api/ai/asr` — 语音识别（multipart 上传录音 + `format` 参数） +- `GET/POST /api/playlist` · `POST /upload` · `GET /media` — 媒体与播放列表 +- `POST /api/display/command` — 管理端控制指令（转 MQTT 广播） +- `GET /api/events` — SSE 兼容通道（MQTT 不可用时的前端回退） + +## 说明 + +- 大屏数据由后端模拟引擎产生（`sim_engine.py`，与原前端 `parkData.js` 逻辑一致）；前端离线时也有本地兜底 +- 媒体文件存放于 `backend/media/`，`/file/...` 直接返回 +- 安全：`backend/.env` 与根 `.env.local` 已加入 `.gitignore`，含阿里云密钥与 MQTT 凭据，勿提交 diff --git a/backend/app/__init__.py b/backend/app/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/ai_tools.py b/backend/app/ai_tools.py new file mode 100644 index 0000000..ce9dc51 --- /dev/null +++ b/backend/app/ai_tools.py @@ -0,0 +1,174 @@ +# -*- coding: utf-8 -*- +"""AI 助手工具调用引擎 + 后端收到对话 → 规则引擎判断意图 → 产出文字回复 + 工具调用列表 + 工具执行时通过 MQTT 广播 opc/display/command，前端（所有大屏）同步响应 + 工具：navigate（切页） / control（媒体控制） / alert（通知） / show_card（展示卡片） +""" + +from .mqtt import hub + +# ---------------- 工具执行 ---------------- + +def execute_tool(tool): + """执行一个工具调用：发布 MQTT 控制指令，返回是否发布成功""" + t = tool.get("type") + params = tool.get("params") or {} + if t == "navigate": + return hub.publish_command("navigate", {"page": params.get("page", "home")}).get("published", False) + if t == "control": + action = params.get("action") + if action in ("play", "pause", "next", "prev"): + return hub.publish_command(action).get("published", False) + if action == "set_mode": + return hub.publish_command("set_mode", {"mode": params.get("mode", "auto")}).get("published", False) + return False + if t == "alert": + return hub.publish_command("alert", {"title": params.get("title", "提示"), "content": params.get("content", "")}).get("published", False) + if t == "show_card": + return hub.publish_command("show_card", params).get("published", False) + return False + + +def run_tools(tools): + """执行一组工具，返回 [{type, ok}] 并汇总是否全部发布成功""" + results = [] + all_ok = True + for tool in tools or []: + ok = bool(execute_tool(tool)) + results.append({"type": tool.get("type"), "ok": ok}) + all_ok = all_ok and ok + return results, all_ok + + +# ---------------- 意图 → 回复 + 工具 ---------------- + +PAGES = { + "home": "/", "数据大屏": "/", "首页": "/", + "twin": "/twin", "数字孪生": "/twin", "3d": "/twin", "孪生": "/twin", + "ai": "/ai", "ai助手": "/ai", "智能助手": "/ai", + "screen": "/screen", "媒体": "/screen", "轮播": "/screen", "媒体轮播": "/screen", +} + +RULES = [ + { + "match": ["入驻", "申请", "入孵", "入园", "如何加入", "怎样加入"], + "reply": "入驻流程如下：\n\n1. 提交入驻申请（线上表单或到园区服务中心现场办理）\n2. 项目评审（园区组织专家对项目可行性、团队背景进行评估）\n3. 签订入驻协议，办理入驻手续\n4. 安排办公场地，对接创业导师与孵化服务\n\n目前园区在园项目 158 家，累计孵化企业 208 余家。如需协助，可直接联系园区服务中心。", + "tools": [{"type": "show_card", "params": {"card": "overview"}}], + }, + { + "match": ["政策", "补贴", "优惠", "扶持", "减免", "奖励", "资助"], + "reply": "园区政策服务覆盖「七位一体」中的政策维度：\n\n· 场地租金减免：符合条件的大学生创业项目可享受场地优惠\n· 创业补贴：协助对接省、市两级创业补贴与一次性创业资助\n· 税费优惠：对接小微企业所得税减免、增值税优惠等政策\n· 项目申报：指导高企认定（目前在园高新技术企业 32 家）、科技型中小企业备案\n\n更多政策细节可咨询园区政策服务窗口。", + "tools": [], + }, + { + "match": ["场地", "办公室", "工位", "租金", "收费", "面积", "多少钱", "价格"], + "reply": "园区总建筑面积 1.2 万㎡，按功能划分为三个区域：\n\n· 加速区（A1–A12）：成长型项目办公室，共 11 间独立办公室 + 1 间园区管理办公室\n· 国际区（I1–I7）：面向国际合作的办公空间（7 间）\n· 成长区（G1–G8）：初创团队成长空间（8 间）\n\n租金按创业项目阶段与政策给予差异化优惠，具体可到园区服务中心咨询。", + "tools": [{"type": "show_card", "params": {"card": "zones"}}], + }, + { + "match": ["企业", "公司", "名录", "名单", "入驻企业", "有哪些企业", "查企业"], + "reply": "园区目前有 39 家入驻企业，分布在三个区域：\n\n· 加速区：云南派音人工智能科技、米勒克尔蓝宝石珠宝、云南宸中低空经济等 9 家\n· 国际区：仰光客厅、中越生物医疗、酷享野农AI农业等 7 家\n· 成长区：Facebook越南跨境电商、昆明云韵体育、云南星瑞航空等 8 家\n\n我已在屏幕上为您展示企业分布卡片。", + "tools": [{"type": "show_card", "params": {"card": "companies"}}], + }, + { + "match": ["融资", "投资", "资金", "贷款", "估值", "资本"], + "reply": "园区融资服务包含：\n\n· 融资对接：定期组织路演与投资机构对接活动\n· 孵化估值：累计孵化企业估值约 5.2 亿元\n· 金融支持：协助对接银行创业贷款、政府创业担保贷款\n· 财务辅导：提供融资方案设计与商业计划书辅导", + "tools": [], + }, + { + "match": ["就业", "招聘", "岗位", "人才", "用工"], + "reply": "园区累计带动就业 2,186 人（其中高校毕业生 1,680 人，实习岗位 506 个）。\n\n· 企业招聘：在驻企业持续发布岗位\n· 人才对接：与在昆高校共建实习实训基地\n· 创业带动：园区鼓励以创业带动就业", + "tools": [], + }, + { + "match": ["导师", "培训", "课程", "辅导", "孵化服务", "孵化器"], + "reply": "园区配备创业导师 58 位，提供全周期孵化服务：\n\n· 一对一辅导：创业导师定期坐诊，覆盖商业模式、法律财税、市场营销\n· 培训课程：创业训练营、行业专题沙龙、政策解读会\n· 资源对接：技术、供应链、渠道等产业资源链接\n· 公共服务：工商注册、知识产权、法律咨询一站式代办", + "tools": [], + }, + { + "match": ["AI", "模型", "算力", "tokens", "token", "工具", "智能", "赋能", "大模型"], + "reply": "园区 AI 赋能服务是「七位一体」的核心特色：\n\n· 大模型推理：接入 DeepSeek-V3、通义千问、智谱 GLM-4、豆包、讯飞星火等多模型\n· 工具调用：文档生成、数据查询、图像创作、代码执行、语音合成等智能工具\n· 算力与成本：实时提供 token 消耗统计与速率监控\n\n今日园区 AI 推理任务持续运行，服务节点 12/12 在线。", + "tools": [], + }, + { + "match": ["加速区", "国际区", "成长区", "分区", "区域", "区别", "布局"], + "reply": "园区按企业成长阶段划分三个区域：\n\n· 加速区（蓝色）：成长型项目独立办公室（A1–A12），在驻 9 家\n· 国际区（青色）：国际合作与跨境业务（I1–I7），在驻 7 家\n· 成长区（绿色）：初创团队共享空间（G1–G8），在驻 8 家\n\n园区管理办公室位于加速区 M 房间。", + "tools": [{"type": "show_card", "params": {"card": "zones"}}], + }, + { + "match": ["切", "去", "打开", "显示", "进入"], + "reply": None, # 由下方页面/控制规则补充 + }, + { + "match": ["你好", "您好", "hi", "hello", "嗨", "在吗"], + "reply": "您好！我是 OPC 园区 AI 智能助手。\n\n可以问我：入驻流程、政策扶持、场地收费、AI 赋能、企业名录、融资服务等问题；也可以让我「切换到数字孪生页」「打开媒体轮播」或「展示企业卡片」。", + "tools": [], + }, + { + "match": ["谢谢", "感谢", "好的", "明白"], + "reply": "不客气，随时为您服务。您也可以让我展示园区数据卡片，或切换到任意展示页面。", + "tools": [], + }, +] + +DEFAULT_REPLY = "园区提供「空间 + 孵化 + 融资 + 政策 + 资源 + AI 赋能 + 综合服务」七位一体服务，在园项目 158 家，累计带动就业 2,186 人，累计营收 2.08 亿元。\n\n您可以这样问我：\n· 如何申请入驻园区？\n· 展示入驻企业卡片\n· 切换到数字孪生页面" + + +def _detect_page(text): + for key, path in PAGES.items(): + if key in text: + return path + return None + + +def _detect_control(text): + if any(k in text for k in ["播放", "继续播放", "开始播放"]): + return "play" + if any(k in text for k in ["暂停", "停止播放"]): + return "pause" + if any(k in text for k in ["下一个", "下一张", "下一屏", "切换下一"]): + return "next" + if any(k in text for k in ["上一个", "上一张", "上一屏", "切换上一"]): + return "prev" + return None + + +def run_chat(messages): + """输入对话消息列表（[{"role","content"}]），返回 {reply, tools}""" + text = "" + for m in reversed(messages or []): + if m.get("role") in ("user", "me"): + text = (m.get("content") or "").strip() + break + + reply = None + tools = [] + + # 1) 页面切换意图（优先级最高） + page = _detect_page(text) + if page: + label = {"/": "数据大屏", "/twin": "数字孪生", "/ai": "AI 助手", "/screen": "媒体轮播"}.get(page, page) + reply = f"好的，已为您切换到「{label}」页面。" + tools = [{"type": "navigate", "params": {"page": page}}] + return {"reply": reply, "tools": tools} + + # 2) 媒体控制意图 + ctrl = _detect_control(text) + if ctrl: + names = {"play": "播放", "pause": "暂停", "next": "切换下一项", "prev": "切换上一项"} + reply = f"好的，已执行：{names[ctrl]}。" + tools = [{"type": "control", "params": {"action": ctrl}}] + return {"reply": reply, "tools": tools} + + # 3) 知识库规则 + for rule in RULES: + if any(k in text for k in rule["match"]): + reply = rule["reply"] + tools = rule["tools"] + break + + if reply is None: + reply = DEFAULT_REPLY + + # 工具已在后端通过 MQTT 广播；返回值供请求端本地同步执行 + return {"reply": reply, "tools": tools} diff --git a/backend/app/asr.py b/backend/app/asr.py new file mode 100644 index 0000000..b6be959 --- /dev/null +++ b/backend/app/asr.py @@ -0,0 +1,93 @@ +# -*- coding: utf-8 -*- +"""语音识别 —— 阿里云 DashScope paraformer-realtime-v2（流式） + 前端录音上传（m4a/wav/ogg/opus/pcm）→ 这里转写为文本 +""" + +import logging +import os +import time + +import certifi + +# macOS 系统 Python 无系统 CA：必须在导入 dashscope 之前设置， +# aiohttp 才会使用 certifi 根证书（否则 WS 连接报 SSL 证书错误） +os.environ.setdefault("SSL_CERT_FILE", certifi.where()) + +import dashscope # noqa: E402 +from dashscope.audio.asr import Recognition, RecognitionCallback # noqa: E402 + +from .config import settings # noqa: E402 + +log = logging.getLogger("dpm.asr") + + +def _err_text(result): + """安全提取 RecognitionResult 的错误描述（其 __str__ 有缺陷）""" + for attr in ("message", "code"): + v = getattr(result, attr, None) + if v: + return f"{attr}={v}" + return repr(result) + +# 前端 MediaRecorder 可能产生的容器/编码 → paraformer 格式名 +FORMAT_ALIASES = { + "mp4": "m4a", "m4a": "m4a", "aac": "m4a", + "webm": "ogg", "opus": "opus", "ogg": "ogg", + "wav": "wav", "pcm": "pcm", "mp3": "mp3", +} + +# m4a/mp3 等压缩格式采样率由服务端自动识别 +_AUTO_SAMPLE_FORMATS = {"m4a", "mp3", "ogg", "opus", "wav"} + + +class _Callback(RecognitionCallback): + def __init__(self): + self.sentences = [] + self.error = None + + def on_message(self, message): + try: + header = message.get("header", {}) + if header.get("action") != "result": + return + payload = message.get("payload", {}) + sentences = payload.get("sentence", {}).get("sentences") or [] + for s in sentences: + if s.get("sentence_end"): + self.sentences.append(s.get("text", "")) + except Exception as e: # noqa: BLE001 + log.warning("ASR 消息解析异常: %s", e) + + def on_error(self, result): + self.error = result + log.warning("ASR 错误: %s", _err_text(result)) + + +def transcribe(audio_bytes: bytes, fmt: str = "m4a") -> str: + """上传音频字节 → 返回转写文本（空串表示未识别到内容）""" + if not settings.DASHSCOPE_API_KEY: + raise RuntimeError("未配置 DASHSCOPE_API_KEY，无法使用阿里云语音识别") + + dashscope.api_key = settings.DASHSCOPE_API_KEY + fmt = FORMAT_ALIASES.get((fmt or "m4a").lower().lstrip("."), "m4a") + + cb = _Callback() + rec = Recognition( + model=settings.ASR_MODEL, + format=fmt, + sample_rate=16000 if fmt in ("pcm", "wav") else 0, # 压缩格式自动识别 + callback=cb, + ) + + # 分块发送，模拟流式（适当间隔，避免触发服务端 batching 报错） + rec.start() + chunk = 16 * 1024 + for i in range(0, len(audio_bytes), chunk): + rec.send_audio_frame(audio_bytes[i:i + chunk]) + time.sleep(0.08) + time.sleep(0.5) # 等待尾部识别 + rec.stop() + + if cb.error: + raise RuntimeError(f"阿里云语音识别失败: {_err_text(cb.error)}") + return "".join(cb.sentences).strip() diff --git a/backend/app/config.py b/backend/app/config.py new file mode 100644 index 0000000..6e465e1 --- /dev/null +++ b/backend/app/config.py @@ -0,0 +1,69 @@ +# -*- coding: utf-8 -*- +"""OPC 智能园区后端 —— 全局配置（backend/.env 可覆盖，未配置时用默认值）""" + +import os +from pathlib import Path + +BASE_DIR = Path(__file__).resolve().parent.parent # backend/ + + +def _load_dotenv(path): + """极简 .env 解析：KEY=VALUE，支持 # 注释与引号""" + if not Path(path).exists(): + return + for raw in Path(path).read_text("utf-8").splitlines(): + line = raw.strip() + if not line or line.startswith("#") or "=" not in line: + continue + key, _, value = line.partition("=") + key = key.strip() + value = value.strip().strip('"').strip("'") + if key and key not in os.environ: + os.environ[key] = value + + +_load_dotenv(BASE_DIR / ".env") + + +def _env(key, default): + return os.getenv(key, default) + + +class Settings: + # ---- HTTP ---- + HOST = _env("DPM_HOST", _env("FASTAPI_HOST", "0.0.0.0")) + PORT = int(_env("DPM_PORT", _env("FASTAPI_PORT", "8000"))) + + # ---- 数据目录 ---- + MEDIA_DIR = Path(_env("DPM_MEDIA_DIR", str(BASE_DIR / "media"))) + DATA_FILE = Path(_env("DPM_DATA_FILE", str(BASE_DIR / "data.json"))) + DIST_DIR = Path(_env("DPM_DIST_DIR", str(BASE_DIR.parent / "dist"))) # 前端构建产物（可选托管） + + # ---- MQTT（优先使用 .env 中的局域网 Broker 配置） ---- + MQTT_ENABLED = _env("DPM_MQTT_ENABLED", "1") == "1" + MQTT_HOST = _env("DPM_MQTT_HOST", _env("MQTT_BROKER_HOST", "127.0.0.1")) + MQTT_PORT = int(_env("DPM_MQTT_PORT", _env("MQTT_BROKER_PORT", "1883"))) + MQTT_USERNAME = _env("DPM_MQTT_USERNAME", _env("MQTT_USERNAME", "")) or None + MQTT_PASSWORD = _env("DPM_MQTT_PASSWORD", _env("MQTT_PASSWORD", "")) or None + MQTT_CLIENT_ID = _env("DPM_MQTT_CLIENT_ID", "dpm-backend") + # 前端 WebSocket 接入地址（默认按 .env 的 broker 主机 + EMQX 常规 ws 端口） + MQTT_WS_URL = _env( + "DPM_MQTT_WS", + f"ws://{_env('MQTT_PUBLIC_HOST', _env('MQTT_BROKER_HOST', 'localhost'))}:8083/mqtt", + ) + MQTT_TICK_INTERVAL = float(_env("DPM_MQTT_TICK_INTERVAL", "2.2")) + + # ---- 主题 ---- + TOPIC_COMMAND = _env("DPM_TOPIC_COMMAND", "opc/display/command") + TOPIC_TICK = _env("DPM_TOPIC_TICK", "opc/dashboard/tick") + TOPIC_ACK = _env("DPM_TOPIC_ACK", "opc/display/ack") + + # ---- 阿里云 DashScope（LLM + 语音识别） ---- + DASHSCOPE_API_KEY = _env("DASHSCOPE_API_KEY", "") + LLM_MODEL = _env("DPM_LLM_MODEL", "qwen-plus") # 通义千问 + ASR_MODEL = _env("DPM_ASR_MODEL", "paraformer-realtime-v2") # 流式语音识别 + LLM_BASE_URL = _env("DPM_LLM_BASE_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1") + ASR_TIMEOUT = float(_env("DPM_ASR_TIMEOUT", "30")) + + +settings = Settings() diff --git a/backend/app/event_bus.py b/backend/app/event_bus.py new file mode 100644 index 0000000..6b0f054 --- /dev/null +++ b/backend/app/event_bus.py @@ -0,0 +1,44 @@ +# -*- coding: utf-8 -*- +"""SSE 事件总线 —— 兼容旧通道（前端 MQTT 不可用时回退） + 所有 MQTT 控制指令同时推送到 SSE /api/events +""" + +import asyncio +import json + + +class EventBus: + def __init__(self): + self._queues = set() + self._loop = None + + def set_loop(self, loop): + self._loop = loop + + def subscribe(self): + q = asyncio.Queue(maxsize=256) + self._queues.add(q) + return q + + def unsubscribe(self, q): + self._queues.discard(q) + + def emit(self, payload: dict): + """线程安全：从任意线程广播事件""" + if not self._loop: + return + try: + asyncio.run_coroutine_threadsafe(self._emit(payload), self._loop) + except Exception: # noqa: BLE001 + pass + + async def _emit(self, payload): + data = json.dumps(payload, ensure_ascii=False) + for q in list(self._queues): + try: + q.put_nowait(data) + except asyncio.QueueFull: + pass + + +bus = EventBus() diff --git a/backend/app/llm.py b/backend/app/llm.py new file mode 100644 index 0000000..da762ba --- /dev/null +++ b/backend/app/llm.py @@ -0,0 +1,197 @@ +# -*- coding: utf-8 -*- +"""AI 对话引擎 —— 阿里云 DashScope（通义千问）+ 函数调用 + 工具调用执行后通过 MQTT 广播，所有大屏同步响应 + DashScope 不可用时自动回退本地规则引擎（离线兜底） +""" + +import json +import logging +import ssl +import urllib.error +import urllib.request + +import certifi + +from .config import settings + +log = logging.getLogger("dpm.llm") + +# macOS 系统 Python 无系统 CA，使用 certifi 提供的根证书 +_SSL_CTX = ssl.create_default_context(cafile=certifi.where()) + +SYSTEM_PROMPT = ( + "你是「昆明市大学生创业园 · OPC 智能园区」的 AI 智能助手，运行在大屏展播系统上。" + "园区提供空间、孵化、融资、政策、资源、AI 赋能、综合服务七位一体服务，" + "在园项目 158 家，累计带动就业 2,186 人，累计营收 2.08 亿元。" + "当用户要求「切换页面 / 控制播放 / 展示卡片 / 弹出通知」时，必须调用对应工具；" + "其余园区相关问题用简洁、专业的中文回答，可适当使用列表。" +) + +# 暴露给大模型的工具定义（执行时经 MQTT 广播到前端） +TOOLS = [ + { + "type": "function", + "function": { + "name": "navigate_page", + "description": "切换大屏展示页面（数据大屏 / 数字孪生 / AI 助手 / 媒体轮播）", + "parameters": { + "type": "object", + "properties": { + "page": {"type": "string", "enum": ["/", "/twin", "/ai", "/screen"], + "description": "目标页面路径"}, + }, + "required": ["page"], + }, + }, + }, + { + "type": "function", + "function": { + "name": "media_control", + "description": "控制媒体播放（播放/暂停/下一项/上一项）", + "parameters": { + "type": "object", + "properties": { + "action": {"type": "string", "enum": ["play", "pause", "next", "prev"]}, + }, + "required": ["action"], + }, + }, + }, + { + "type": "function", + "function": { + "name": "show_card", + "description": "在大屏上展示信息卡片（企业分布 / 分区介绍 / 园区总览 / 自定义内容）", + "parameters": { + "type": "object", + "properties": { + "card": {"type": "string", "enum": ["companies", "zones", "overview", "custom"]}, + "title": {"type": "string"}, + "content": {"type": "string"}, + }, + "required": ["card"], + }, + }, + }, + { + "type": "function", + "function": { + "name": "send_alert", + "description": "在大屏上弹出通知提示", + "parameters": { + "type": "object", + "properties": { + "title": {"type": "string"}, + "content": {"type": "string"}, + }, + "required": ["title", "content"], + }, + }, + }, +] + +_TOOL_MAP = { + "navigate_page": "navigate", + "media_control": "control", + "show_card": "show_card", + "send_alert": "alert", +} + + +def _chat_once(messages, with_tools=True): + payload = { + "model": settings.LLM_MODEL, + "messages": messages, + "temperature": 0.6, + } + if with_tools: + payload["tools"] = TOOLS + req = urllib.request.Request( + f"{settings.LLM_BASE_URL}/chat/completions", + data=json.dumps(payload, ensure_ascii=False).encode("utf-8"), + headers={ + "Content-Type": "application/json", + "Authorization": f"Bearer {settings.DASHSCOPE_API_KEY}", + }, + ) + with urllib.request.urlopen(req, timeout=60, context=_SSL_CTX) as resp: + return json.loads(resp.read().decode("utf-8")) + + +def _fallback(messages): + """DashScope 不可用时回退本地规则引擎""" + from .ai_tools import run_chat as rule_run + + result = rule_run(messages) + # 规则引擎产出的工具同样执行（MQTT 广播），并汇总发布结果 + _, all_ok = _exec_all(result.get("tools", [])) + result["model"] = "rule-engine" + result["mqtt_published"] = all_ok + return result + + +def _exec_all(tools): + """执行工具列表，返回 (results, all_ok)""" + from .ai_tools import run_tools + + results, all_ok = run_tools(tools) + return results, all_ok + + +def run_chat(messages): + """入口：{reply, tools, model} + tools 已在后端执行（MQTT 广播），返回值供请求端本地同步执行""" + if not settings.DASHSCOPE_API_KEY: + log.warning("未配置 DASHSCOPE_API_KEY，使用本地规则引擎") + return _fallback(messages) + + msgs = [{"role": "system", "content": SYSTEM_PROMPT}] + [ + {"role": m.get("role") == "me" and "user" or m.get("role", "user"), "content": m.get("content", "")} + for m in (messages or []) + ] + + try: + data = _chat_once(msgs) + choice = data["choices"][0]["message"] + reply = choice.get("content") or "" + tool_calls = choice.get("tool_calls") or [] + executed = [] + + if tool_calls: + for tc in tool_calls: + fn = tc.get("function", {}) + name = fn.get("name", "") + try: + args = json.loads(fn.get("arguments") or "{}") + except json.JSONDecodeError: + args = {} + tool = {"type": _TOOL_MAP.get(name, name), "params": args} + executed.append(tool) + msgs.append({"role": "assistant", "content": None, "tool_calls": tool_calls}) + msgs.append({ + "role": "tool", + "tool_call_id": tc.get("id", ""), + "content": json.dumps({"ok": True}, ensure_ascii=False), + }) + # 工具执行（MQTT 广播），并汇总发布结果 + _, all_ok = _exec_all(executed) + # 二次调用：携带工具结果生成最终回复 + try: + data2 = _chat_once(msgs, with_tools=False) + reply = data2["choices"][0]["message"].get("content") or reply + except Exception as e: # noqa: BLE001 + log.warning("LLM 二次调用失败（保留工具回复）: %s", e) + else: + all_ok = True + + if not reply: + reply = "已完成操作。您还可以让我切换页面、控制播放或展示园区卡片。" + + return {"reply": reply, "tools": executed, "model": settings.LLM_MODEL, "mqtt_published": all_ok} + except urllib.error.HTTPError as e: + log.warning("DashScope HTTP %s: %s", e.code, e.read()[:300]) + except Exception as e: # noqa: BLE001 + log.warning("DashScope 调用失败，回退规则引擎: %s", e) + + return _fallback(messages) diff --git a/backend/app/main.py b/backend/app/main.py new file mode 100644 index 0000000..564ba4f --- /dev/null +++ b/backend/app/main.py @@ -0,0 +1,94 @@ +# -*- coding: utf-8 -*- +"""OPC 智能园区后端 —— FastAPI 入口 + 启动：uvicorn app.main:app --host 0.0.0.0 --port 8000 + 或：python main.py +""" + +import asyncio +import logging +import threading +import time +from contextlib import asynccontextmanager +from pathlib import Path + +from fastapi import FastAPI, Request +from fastapi.middleware.cors import CORSMiddleware +from fastapi.responses import FileResponse, JSONResponse +from fastapi.staticfiles import StaticFiles + +from .config import settings +from .event_bus import bus +from .mqtt import hub +from .routers import router +from .sim_engine import sim_engine + +logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(name)s %(message)s") +log = logging.getLogger("dpm.main") + +DIST = Path(settings.DIST_DIR) + + +@asynccontextmanager +async def lifespan(app: FastAPI): + # 启动准备 + settings.MEDIA_DIR.mkdir(parents=True, exist_ok=True) + bus.set_loop(asyncio.get_running_loop()) + hub.start() + + stop = threading.Event() + + def tick_loop(): + """数据引擎每 2.2s 推进一次；MQTT 连接时同步推送快照""" + while not stop.is_set(): + try: + snap = sim_engine.tick() + hub.publish_tick(snap) + except Exception as e: # noqa: BLE001 + log.warning("数据 tick 异常: %s", e) + stop.wait(settings.MQTT_TICK_INTERVAL) + + threading.Thread(target=tick_loop, daemon=True).start() + log.info("OPC 智能园区后端启动于 http://%s:%s", settings.HOST, settings.PORT) + if settings.MQTT_ENABLED: + log.info("MQTT Broker: %s:%s（前端 WS: %s）", settings.MQTT_HOST, settings.MQTT_PORT, settings.MQTT_WS_URL) + try: + yield + finally: + stop.set() + hub.stop() + log.info("OPC 智能园区后端已停止") + + +app = FastAPI(title="OPC 智能园区后端", version="1.0.0", lifespan=lifespan) + +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_methods=["*"], + allow_headers=["*"], +) + +app.include_router(router) + +# 媒体资源静态服务（上传/播放的文件） +settings.MEDIA_DIR.mkdir(parents=True, exist_ok=True) +app.mount("/file", StaticFiles(directory=str(settings.MEDIA_DIR)), name="media") + + +# ---------- 前端静态托管 + SPA 回退（浏览器直接访问 :8000 即可） ---------- + +@app.get("/{path:path}", include_in_schema=False) +async def spa_fallback(path: str): + if not DIST.exists(): + return JSONResponse({"detail": "前端未构建（dist 目录不存在）"}, status_code=404) + dist = DIST.resolve() + if not path: + target = dist / "index.html" + else: + target = (dist / path).resolve() + if target.is_file() and target.is_relative_to(dist): + return FileResponse(target) + index = dist / "index.html" + if index.exists(): + return FileResponse(index) + return JSONResponse({"detail": "Not Found"}, status_code=404) diff --git a/backend/app/mqtt.py b/backend/app/mqtt.py new file mode 100644 index 0000000..6f06f49 --- /dev/null +++ b/backend/app/mqtt.py @@ -0,0 +1,105 @@ +# -*- coding: utf-8 -*- +"""MQTT 发布中心 —— 后端 → 前端控制通道 + 页面控制 / 媒体控制 / 卡片展示指令统一走 opc/display/command + 数据快照按 DPM_MQTT_TICK_INTERVAL 推送 opc/dashboard/tick +""" + +import json +import logging +import threading +import time +import uuid + +import paho.mqtt.client as mqtt + +from .config import settings +from .event_bus import bus + +log = logging.getLogger("dpm.mqtt") + + +def new_cmd_id(): + return uuid.uuid4().hex[:12] + + +class MqttHub: + def __init__(self): + self.client = None + self.connected = False + self._lock = threading.RLock() + + # ---------- 生命周期 ---------- + def start(self): + if not settings.MQTT_ENABLED: + log.info("MQTT 已禁用（DPM_MQTT_ENABLED=0）") + return + try: + self.client = mqtt.Client( + client_id=settings.MQTT_CLIENT_ID, + clean_session=True, + protocol=mqtt.MQTTv311, + ) + if settings.MQTT_USERNAME: + self.client.username_pw_set(settings.MQTT_USERNAME, settings.MQTT_PASSWORD) + self.client.on_connect = self._on_connect + self.client.on_disconnect = self._on_disconnect + self.client.connect_async(settings.MQTT_HOST, settings.MQTT_PORT, keepalive=30) + self.client.loop_start() + log.info("MQTT 连接中 %s:%s ...", settings.MQTT_HOST, settings.MQTT_PORT) + except Exception as e: # noqa: BLE001 + log.warning("MQTT 初始化失败（数据 API 不受影响）: %s", e) + + def stop(self): + if self.client: + try: + self.client.loop_stop() + self.client.disconnect() + except Exception: # noqa: BLE001 + pass + self.client = None + + def _on_connect(self, client, userdata, flags, rc): + if rc == 0: + self.connected = True + log.info("MQTT 已连接 %s:%s", settings.MQTT_HOST, settings.MQTT_PORT) + else: + log.warning("MQTT 连接失败 rc=%s", rc) + + def _on_disconnect(self, client, userdata, rc): + self.connected = False + if rc != 0: + log.warning("MQTT 断开（rc=%s），自动重连中...", rc) + + # ---------- 发布 ---------- + def publish(self, topic, payload, qos=1, retain=False): + if not self.client or not self.connected: + log.debug("MQTT 未连接，丢弃发布 %s", topic) + return False + try: + info = self.client.publish(topic, json.dumps(payload, ensure_ascii=False), qos=qos, retain=retain) + return info.rc == mqtt.MQTT_ERR_SUCCESS + except Exception as e: # noqa: BLE001 + log.warning("MQTT 发布失败: %s", e) + return False + + def publish_command(self, action, params=None): + """统一指令信封：{cmd_id, ts, action, params, published} + MQTT 广播 + SSE 兼容推送；published 标记是否真正发布成功""" + payload = { + "cmd_id": new_cmd_id(), + "ts": int(time.time() * 1000), + "action": action, + "params": params or {}, + } + ok = self.publish(settings.TOPIC_COMMAND, payload) + payload["published"] = ok + if ok: + bus.emit(payload) # SSE 兼容通道（仅发布成功时推送） + return payload + + def publish_tick(self, snapshot): + payload = {"ts": int(time.time() * 1000), "snapshot": snapshot} + self.publish(settings.TOPIC_TICK, payload, qos=0) + + +hub = MqttHub() diff --git a/backend/app/routers.py b/backend/app/routers.py new file mode 100644 index 0000000..f03d553 --- /dev/null +++ b/backend/app/routers.py @@ -0,0 +1,383 @@ +# -*- coding: utf-8 -*- +"""全部 REST 路由 —— 数据 / 媒体 / 播放列表 / 设置 / AI / 展示控制""" + +import asyncio +import json +import logging +import time +from pathlib import Path + +from fastapi import APIRouter, Request, UploadFile, File +from fastapi.responses import JSONResponse, StreamingResponse +from pydantic import BaseModel, Field + +from .ai_tools import run_chat, run_tools +from .asr import transcribe as asr_transcribe +from .config import settings +from .event_bus import bus +from .llm import run_chat as llm_run_chat +from .mqtt import hub +from .sim_engine import sim_engine +from .storage import storage + +log = logging.getLogger("dpm.api") + +router = APIRouter() + +ALLOWED_EXT = {".mp4", ".mkv", ".avi", ".jpg", ".jpeg", ".png"} + + +def _media_type(path): + lower = path.lower() + if lower.endswith((".mp4", ".mkv", ".avi")): + return "video" + return "image" + + +# ==================== 数据模型 ==================== + +class SettingsBody(BaseModel): + volume: int | None = None + play_mode: str | None = None + image_duration: int | None = None + fullscreen: bool | None = None + autostart: bool | None = None + username: str | None = None + password: str | None = None + + +class ActionBody(BaseModel): + action: str + + +class PathBody(BaseModel): + path: str + + +class UrlBody(BaseModel): + url: str + + +class StatePayload(BaseModel): + status: str = "" + index: int = 0 + name: str = "" + media_type: str = "" + + +class StateBody(BaseModel): + state: StatePayload + + +class DisplayCommandBody(BaseModel): + action: str + params: dict = Field(default_factory=dict) + + +class ChatMessage(BaseModel): + role: str + content: str + + +class ChatBody(BaseModel): + messages: list[ChatMessage] + + +# ==================== 认证 / 设置 ==================== + +@router.post("/api/login") +async def login(request: Request): + form = await request.form() + s = storage.get_settings() + return JSONResponse({"success": form.get("username") == s["username"] and form.get("password") == s["password"]}) + + +@router.get("/api/settings") +async def get_settings(): + s = storage.get_settings() + return {k: s[k] for k in ("volume", "play_mode", "image_duration", "fullscreen", "autostart")} + + +@router.post("/api/settings") +async def update_settings(body: SettingsBody): + storage.update_settings(**body.model_dump(exclude_none=True)) + s = storage.get_settings() + hub.publish_command("settings_changed", {"volume": s["volume"], "play_mode": s["play_mode"]}) + return {"ok": True} + + +# ==================== 媒体 ==================== + +def _list_media(): + files = [] + media_dir = Path(settings.MEDIA_DIR) + if media_dir.exists(): + for p in sorted(media_dir.iterdir()): + if not p.is_file() or p.suffix.lower() not in ALLOWED_EXT: + continue + files.append({ + "name": p.name, "relative_path": p.name, + "type": _media_type(p.name), "url": f"/file/{p.name}", "source": "local", + }) + for item in storage.get_url_media(): + files.append({ + "name": item.get("name", item.get("url", "")), + "relative_path": item.get("url", ""), + "type": item.get("type", "image"), + "url": item.get("url", ""), + "source": "url", + }) + return {"files": files} + + +@router.get("/media") +async def list_media(): + return _list_media() + + +@router.post("/upload") +async def upload(file: UploadFile = File(...)): + name = file.filename or "file" + ext = Path(name).suffix.lower() + if ext not in ALLOWED_EXT: + return JSONResponse({"ok": False, "error": "不支持的文件类型"}, status_code=400) + settings.MEDIA_DIR.mkdir(parents=True, exist_ok=True) + stem = Path(name).stem + new_name = f"{stem}_{time.strftime('%Y%m%d%H%M%S')}{ext}" + save_path = settings.MEDIA_DIR / new_name + with save_path.open("wb") as f: + while True: + chunk = await file.read(1024 * 1024) + if not chunk: + break + f.write(chunk) + hub.publish_command("playlist_changed") + return {"ok": True, "name": new_name} + + +@router.post("/api/delete") +async def delete_media(body: PathBody): + path = body.path + if not path.startswith(("http://", "https://")): + target = settings.MEDIA_DIR / path + try: + if target.exists() and target.is_file(): + target.unlink() + except OSError: + pass + storage.delete_media(path) + hub.publish_command("playlist_changed") + return {"ok": True} + + +@router.post("/api/media/add-url") +async def add_url(body: UrlBody): + url = body.url.strip() + if not url: + return {"ok": False} + name = url.rsplit("/", 1)[-1].split("?", 1)[0] or url + t = _media_type(url) + is_new = storage.add_url_media(url, name, t) + return {"ok": True, "duplicate": None if is_new else True} + + +# ==================== 播放列表 ==================== + +def _playlist_files(): + files = [] + media_dir = Path(settings.MEDIA_DIR) + for item in storage.get_playlist(): + path = item.get("path", "") + if item.get("source") == "url": + files.append({ + "name": item.get("name") or path, + "relative_path": path, "type": _media_type(path), "url": path, "source": "url", + }) + else: + fp = media_dir / path + if fp.exists(): + files.append({ + "name": fp.name, "relative_path": path, + "type": _media_type(path), "url": f"/file/{path}", "source": "local", + }) + s = storage.get_settings() + return {"files": files, "volume": s["volume"], "play_mode": s["play_mode"], "image_duration": s["image_duration"]} + + +@router.get("/api/playlist") +async def get_playlist(): + return _playlist_files() + + +@router.post("/api/playlist/add") +async def add_playlist(body: PathBody): + storage.add_to_playlist(body.path) + hub.publish_command("playlist_changed") + return {"ok": True} + + +@router.post("/api/playlist/remove") +async def remove_playlist(body: PathBody): + storage.remove_from_playlist(body.path) + hub.publish_command("playlist_changed") + return {"ok": True} + + +# ==================== 播放控制 / 状态 ==================== + +_CONTROL_ACTIONS = {"play", "pause", "next", "prev"} + + +@router.post("/api/control") +async def control(body: ActionBody): + if body.action not in _CONTROL_ACTIONS: + return JSONResponse({"ok": False, "error": "action 必须是 play/pause/next/prev"}, status_code=400) + hub.publish_command(body.action) + return {"ok": True, "action": body.action} + + +@router.get("/api/state") +async def get_state(): + return {"state": {"status": "unknown", "index": 0, "name": "", "media_type": ""}} + + +@router.post("/api/state") +async def update_state(body: StateBody): + hub.publish_command("state_update", body.state.model_dump()) + return {"ok": True} + + +@router.post("/api/display-command") +async def display_command(body: ActionBody): + if body.action == "minimize": + hub.publish_command("minimize") + return {"ok": True, "action": "minimize"} + return JSONResponse({"ok": False, "error": "不支持的显示命令"}, status_code=400) + + +# ==================== 数据（大屏全部数据来自后端） ==================== + +@router.get("/api/dashboard/snapshot") +async def dashboard_snapshot(): + return sim_engine.snapshot() + + +@router.get("/api/dashboard/overview") +async def dashboard_overview(): + return sim_engine.snapshot() + + +# ==================== 园区企业 ==================== + +_COMPANIES = [ + {"name": "云南派音人工智能科技", "zone": "加速区", "room": "A1", "color": "#4c8dff"}, + {"name": "米勒克尔蓝宝石珠宝", "zone": "加速区", "room": "A2", "color": "#4c8dff"}, + {"name": "中泰研学合作", "zone": "加速区", "room": "A3", "color": "#4c8dff"}, + {"name": "云南宸中低空经济", "zone": "加速区", "room": "A4", "color": "#4c8dff"}, + {"name": "昆明智海银高文化科技", "zone": "加速区", "room": "A5", "color": "#4c8dff"}, + {"name": "AI机器人大模型训练", "zone": "加速区", "room": "A6", "color": "#4c8dff"}, + {"name": "云南廷秀文旅康养", "zone": "加速区", "room": "A7", "color": "#4c8dff"}, + {"name": "瀚颖AI+教育信息咨询", "zone": "加速区", "room": "A8", "color": "#4c8dff"}, + {"name": "云南大学AI+创业平台", "zone": "加速区", "room": "A9", "color": "#4c8dff"}, + {"name": "仰光客厅", "zone": "国际区", "room": "I1", "color": "#22d3ee"}, + {"name": "云南上古绝学文化", "zone": "国际区", "room": "I2", "color": "#22d3ee"}, + {"name": "中越生物医疗", "zone": "国际区", "room": "I3", "color": "#22d3ee"}, + {"name": "酷享野农AI农业", "zone": "国际区", "room": "I4", "color": "#22d3ee"}, + {"name": "滇缅国际设计", "zone": "国际区", "room": "I5", "color": "#22d3ee"}, + {"name": "昆明舒诺生物科技", "zone": "国际区", "room": "I6", "color": "#22d3ee"}, + {"name": "达岸教育管理", "zone": "国际区", "room": "I7", "color": "#22d3ee"}, + {"name": "Facebook越南跨境电商", "zone": "成长区", "room": "G1", "color": "#34d399"}, + {"name": "研X同行者网络", "zone": "成长区", "room": "G2", "color": "#34d399"}, + {"name": "朵哈·玫瑰特色产业链", "zone": "成长区", "room": "G3", "color": "#34d399"}, + {"name": "昆明云韵体育", "zone": "成长区", "room": "G4", "color": "#34d399"}, + {"name": "南菌优培食用菌", "zone": "成长区", "room": "G5", "color": "#34d399"}, + {"name": "五华区丽裳文化", "zone": "成长区", "room": "G6", "color": "#34d399"}, + {"name": "云南星瑞航空", "zone": "成长区", "room": "G7", "color": "#34d399"}, + {"name": "综合直播私域平台", "zone": "成长区", "room": "G8", "color": "#34d399"}, + {"name": "园区管理办公室", "zone": "园区管理", "room": "M", "color": "#fbbf24"}, +] + + +@router.get("/api/park/companies") +async def park_companies(): + return {"companies": _COMPANIES} + + +@router.get("/api/park/zones") +async def park_zones(): + zones = ["加速区", "国际区", "成长区"] + counts = {z: sum(1 for c in _COMPANIES if c["zone"] == z) for z in zones} + colors = {"加速区": "#4c8dff", "国际区": "#22d3ee", "成长区": "#34d399"} + return {"zones": [{"name": z, "count": counts[z], "color": colors[z]} for z in zones]} + + +# ==================== AI 对话（通义千问 + 工具调用） ==================== + +@router.post("/api/ai/chat") +async def ai_chat(body: ChatBody): + """大模型对话：工具调用（切页/控制/卡片/通知）经 MQTT 广播到所有大屏 + 返回 {reply, tools, model}；tools 供请求端本地同步执行""" + messages = [m.model_dump() for m in body.messages] + result = llm_run_chat(messages) + return result + + +@router.post("/api/ai/asr") +async def ai_asr(file: UploadFile = File(...), format: str = "m4a"): + """语音识别：上传录音 → 阿里云 paraformer 转写为文本""" + data = await file.read() + if not data: + return JSONResponse({"ok": False, "error": "空音频"}, status_code=400) + try: + text = asr_transcribe(data, fmt=format) + return {"ok": True, "text": text} + except Exception as e: # noqa: BLE001 + log.warning("ASR 转写失败: %s", e) + return JSONResponse({"ok": False, "error": str(e)}, status_code=502) + + +# ==================== 展示控制（管理端 → MQTT） ==================== + +_VALID_DISPLAY_ACTIONS = {"navigate", "navigate_rel", "play", "pause", "next", "prev", + "alert", "show_card", "set_mode", "minimize"} + + +@router.post("/api/display/command") +async def display_command_publish(body: DisplayCommandBody): + """管理端/任意客户端通过 REST 发控制指令 → 后端转 MQTT 广播给所有大屏""" + if body.action not in _VALID_DISPLAY_ACTIONS: + return JSONResponse({"ok": False, "error": f"不支持的指令: {body.action}"}, status_code=400) + cmd = hub.publish_command(body.action, body.params) + return {"ok": cmd.get("published", False), "cmd_id": cmd["cmd_id"], "action": body.action, + "mqtt_connected": hub.connected} + + +@router.get("/api/display/state") +async def display_state(): + return { + "mqtt_connected": hub.connected, + "mqtt_host": f"{settings.MQTT_HOST}:{settings.MQTT_PORT}", + "page": None, # 前端可通过 MQTT 回执上报当前页（后续扩展） + } + + +# ==================== SSE 兼容通道（MQTT 不可用时前端回退） ==================== + +@router.get("/api/events") +async def sse_events(request: Request): + q = bus.subscribe() + + async def gen(): + try: + while True: + if await request.is_disconnected(): + break + try: + data = await asyncio.wait_for(q.get(), timeout=15) + yield f"data: {data}\n\n" + except asyncio.TimeoutError: + yield ": keepalive\n\n" + finally: + bus.unsubscribe(q) + + return StreamingResponse(gen(), media_type="text/event-stream") diff --git a/backend/app/sim_engine.py b/backend/app/sim_engine.py new file mode 100644 index 0000000..6825556 --- /dev/null +++ b/backend/app/sim_engine.py @@ -0,0 +1,156 @@ +# -*- coding: utf-8 -*- +"""园区数据模拟引擎 —— 由前端 parkData.js 移植，后端统一产生数据 + 前端通过 GET /api/dashboard/snapshot 获取，或订阅 MQTT opc/dashboard/tick +""" + +import random +import threading +import time + +MODEL_NAMES = ["DeepSeek-V3", "通义千问", "智谱 GLM-4", "豆包", "讯飞星火"] +TOOL_NAMES = ["文档生成", "数据查询", "图像创作", "代码执行", "语音合成"] +COMPANY_NAMES = [ + "云南派音人工智能科技", "米勒克尔蓝宝石珠宝", "中泰研学合作", "云南宸中低空经济", + "昆明智海银高文化科技", "云南廷秀文旅康养", "瀚颖AI+教育信息咨询", + "仰光客厅", "云南上古绝学文化", "中越生物医疗", "酷享野农AI农业", + "滇缅国际设计", "昆明舒诺生物科技", "达岸教育管理", "花仙子园艺肥料", + "研X同行者网络", "鬼才明AI创意工作室", "朵哈·玫瑰特色产业链", "昆明云韵体育", + "南菌优培食用菌", "五华区丽裳文化", "云南星瑞航空", "综合直播私域平台", + "昆明屿澈电商", "蓝智科技", "云品出滇·纸享万家", "启元人工智能科技", +] + + +def _pick(arr): + return arr[random.randrange(len(arr))] + + +def _now_time(): + return time.strftime("%H:%M:%S") + + +def make_series(base, growth, noise, n=30): + out = [] + v = base + for _ in range(n): + v = v * (1 + growth) + (random.random() - 0.5) * noise + out.append(round(max(1, v * 100) / 100, 2)) + return out + + +def gen_event(): + r = random.random + pool = [ + {"icon": "bolt", "text": f"AI 推理任务完成 · 消耗 {round(800 + r() * 9000):,} tokens（{_pick(MODEL_NAMES)}）"}, + {"icon": "wrench", "text": f"工具「{_pick(TOOL_NAMES)}」被调用 {round(10 + r() * 90)} 次"}, + {"icon": "building", "text": f"「{_pick(COMPANY_NAMES)}」提交入驻申请 · 进入评审流程"}, + {"icon": "users", "text": f"「{_pick(COMPANY_NAMES)}」新增招聘岗位 {round(1 + r() * 5)} 个"}, + {"icon": "coin", "text": f"园区企业完成一笔 ¥{(0.5 + r() * 9):.1f}万 交易"}, + {"icon": "robot", "text": f"「{_pick(MODEL_NAMES)}」模型完成一次微调任务"}, + ] + e = _pick(pool) + return {"id": f"{int(time.time()*1000)}-{random.random()}", "icon": e["icon"], "text": e["text"], "time": _now_time()} + + +def init_feed(): + return [ + {"id": 1, "icon": "bolt", "text": "云南派音AI 完成音频向量嵌入任务 · 消耗 12,480 tokens", "time": _now_time()}, + {"id": 2, "icon": "building", "text": "「启元人工智能科技」通过评审 · 正式入驻 OPC 创业空间", "time": _now_time()}, + {"id": 3, "icon": "users", "text": "「昆明舒护安养老服务」新增招聘岗位 2 个", "time": _now_time()}, + {"id": 4, "icon": "coin", "text": "园区企业完成一笔 ¥3.6万 交易", "time": _now_time()}, + ] + + +def init_snapshot(): + return { + "t": 0, + "token": {"today": 128.64, "total": 12840, "rate": 84.6, "series": make_series(82, 0.012, 9)}, + "tools": {"today": 3568, "total": 365204, "success": 98.7}, + "projects": {"inPark": 158, "cum": 208, "todayNew": 2}, + "jobs": {"total": 2186, "todayNew": 3}, + "revenue": {"today": 38.6, "total": 20800, "growth": 8.2, "series": make_series(30, 0.006, 4)}, + "park": {"devices": 98.6, "energy": 386, "people": 127, "desk": 76, "meeting": 3, "nodes": 12}, + "feed": init_feed(), + } + + +def next_snapshot(s): + r = random.random + t_delta = round(0.26 + r() * 0.34, 2) + + token = { + "today": round(s["token"]["today"] + t_delta, 2), + "total": round(s["token"]["total"] + t_delta, 2), + "rate": round(76 + r() * 20, 1), + } + tool_delta = round(13 + r() * 22) + tools = { + "today": s["tools"]["today"] + tool_delta, + "total": s["tools"]["total"] + tool_delta, + "success": round(98.1 + r() * 1.2, 1), + } + rev_delta = round(0.6 + r() * 1.7, 1) + revenue = { + "today": round(s["revenue"]["today"] + rev_delta, 1), + "total": round(s["revenue"]["total"] + rev_delta, 1), + "growth": round(7.2 + r() * 2.2, 1), + } + park = { + "devices": round(97.6 + r() * 1.6, 1), + "energy": round(320 + r() * 130), + "people": round(80 + r() * 95), + "desk": round(62 + r() * 24), + "meeting": round(2 + r() * 4), + "nodes": 12, + } + + projects = dict(s["projects"]) + if r() < 0.055: + projects["todayNew"] += 1 + if r() < 0.035: + projects["inPark"] += 1 + projects["cum"] += 1 + jobs = dict(s["jobs"]) + if r() < 0.08: + jobs["todayNew"] += 1 + if r() < 0.05: + jobs["total"] += 1 + + t_series = list(s["token"]["series"]) + t_series[-1] = round(t_series[-1] + t_delta, 2) + if s["t"] % 12 == 11: + t_series = t_series[1:] + [round(72 + r() * 30, 2)] + token["series"] = t_series + + r_series = list(s["revenue"]["series"]) + r_series[-1] = round(r_series[-1] + rev_delta, 1) + if s["t"] % 12 == 11: + r_series = r_series[1:] + [round(26 + r() * 9, 1)] + revenue["series"] = r_series + + feed = [gen_event()] + s["feed"][:6] if s["t"] % 3 == 2 else s["feed"] + + return { + "t": s["t"] + 1, + "token": token, "tools": tools, "revenue": revenue, + "park": park, "projects": projects, "jobs": jobs, "feed": feed, + } + + +class SimEngine: + """带锁的快照引擎：单例供 API 与 MQTT tick 共用""" + + def __init__(self): + self._lock = threading.RLock() + self._snap = init_snapshot() + + def snapshot(self): + with self._lock: + return dict(self._snap) + + def tick(self): + with self._lock: + self._snap = next_snapshot(self._snap) + return dict(self._snap) + + +sim_engine = SimEngine() diff --git a/backend/app/storage.py b/backend/app/storage.py new file mode 100644 index 0000000..f6271cf --- /dev/null +++ b/backend/app/storage.py @@ -0,0 +1,106 @@ +# -*- coding: utf-8 -*- +"""JSON 持久化：设置 / 播放列表 / URL 媒体（对齐原 Rust storage 语义）""" + +import json +import threading +import time +from pathlib import Path + +from .config import settings + +DEFAULT_SETTINGS = { + "username": "admin", + "password": "123456", + "volume": 80, + "auto_play": True, + "play_mode": "sequential", + "image_duration": 5, + "fullscreen": True, + "autostart": False, +} + + +class Storage: + def __init__(self, data_file: Path): + self.data_file = data_file + self._lock = threading.RLock() + self._data = self._load() + + # ---------- 底层 ---------- + def _load(self): + if self.data_file.exists(): + try: + return json.loads(self.data_file.read_text("utf-8")) + except Exception: + pass + return {"settings": dict(DEFAULT_SETTINGS), "playlist": [], "url_media": []} + + def _save(self): + self.data_file.parent.mkdir(parents=True, exist_ok=True) + tmp = self.data_file.with_suffix(".tmp") + tmp.write_text(json.dumps(self._data, ensure_ascii=False, indent=2), "utf-8") + tmp.replace(self.data_file) + + # ---------- 设置 ---------- + def get_settings(self): + with self._lock: + s = dict(DEFAULT_SETTINGS) + s.update(self._data.get("settings", {})) + return s + + def update_settings(self, **kw): + with self._lock: + s = dict(DEFAULT_SETTINGS) + s.update(self._data.get("settings", {})) + for k, v in kw.items(): + if v is not None and k in s: + s[k] = v + self._data["settings"] = s + self._save() + + # ---------- 播放列表 ---------- + def get_playlist(self): + with self._lock: + return list(self._data.get("playlist", [])) + + def add_to_playlist(self, path): + with self._lock: + items = self._data.setdefault("playlist", []) + if not any(it.get("path") == path for it in items): + items.append({"path": path, "source": None, "name": None}) + self._save() + + def remove_from_playlist(self, path): + with self._lock: + self._data.setdefault("playlist", []) + self._data["playlist"] = [it for it in self._data["playlist"] if it.get("path") != path] + self._save() + + # ---------- URL 媒体 ---------- + def get_url_media(self): + with self._lock: + return list(self._data.get("url_media", [])) + + def add_url_media(self, url, name, media_type): + """返回 True 表示新增，False 表示已存在（重复）""" + with self._lock: + items = self._data.setdefault("url_media", []) + if any(it.get("url") == url for it in items): + return False + items.append({ + "url": url, "name": name, "type": media_type, + "added_at": time.strftime("%Y-%m-%d %H:%M:%S"), + }) + self._save() + return True + + def delete_media(self, path): + with self._lock: + self._data.setdefault("url_media", []) + self._data["url_media"] = [it for it in self._data["url_media"] if it.get("url") != path] + self._data.setdefault("playlist", []) + self._data["playlist"] = [it for it in self._data["playlist"] if it.get("path") != path] + self._save() + + +storage = Storage(settings.DATA_FILE) diff --git a/backend/main.py b/backend/main.py new file 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"node_modules/nanoid": { @@ -2144,6 +2367,16 @@ "dev": true, "license": "MIT" }, + "node_modules/number-allocator": { + "version": "1.0.14", + "resolved": "https://registry.npmmirror.com/number-allocator/-/number-allocator-1.0.14.tgz", + "integrity": "sha512-OrL44UTVAvkKdOdRQZIJpLkAdjXGTRda052sN4sO77bKEzYYqWKMBjQvrJFzqygI99gL6Z4u2xctPW1tB8ErvA==", + "license": "MIT", + "dependencies": { + "debug": "^4.3.1", + "js-sdsl": "4.3.0" + } + }, "node_modules/path-key": { "version": "3.1.1", "resolved": "https://registry.npmmirror.com/path-key/-/path-key-3.1.1.tgz", @@ -2205,6 +2438,21 @@ "integrity": "sha512-choctRBIV9EMT9WGAZHn3V7t0Z2pMQyl0EZE6pFc/6ml3ssw7Dlf/oAOvFwjm1HVsqfQN8GfeFyJ+d8tRzqueQ==", "license": "ISC" }, + "node_modules/process": { + "version": "0.11.10", + "resolved": "https://registry.npmmirror.com/process/-/process-0.11.10.tgz", + "integrity": "sha512-cdGef/drWFoydD1JsMzuFf8100nZl+GT+yacc2bEced5f9Rjk4z+WtFUTBu9PhOi9j/jfmBPu0mMEY4wIdAF8A==", + "license": "MIT", + "engines": { + 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"node": "^12.22.0 || ^14.17.0 || >=16.0.0" + } + }, "node_modules/require-from-string": { "version": "2.0.2", "resolved": "https://registry.npmmirror.com/require-from-string/-/require-from-string-2.0.2.tgz", @@ -2340,6 +2604,12 @@ "integrity": "sha512-AgZ3UOZm3YndfrJ4OYjgrT7bmCm/1iqkjvEfH/oYjzh6PD2qw4QuT3jjnXIrpdt4MTpMXclMT3lXbmRY+XRakw==", "license": "MIT" }, + "node_modules/rfdc": { + "version": "1.4.1", + "resolved": "https://registry.npmmirror.com/rfdc/-/rfdc-1.4.1.tgz", + "integrity": "sha512-q1b3N5QkRUWUl7iyylaaj3kOpIT0N2i9MqIEQXP73GVsN9cw3fdx8X63cEmWhJGi2PPCF23Ijp7ktmd39rawIA==", + "license": "MIT" + }, "node_modules/rollup": { "version": "4.60.3", "resolved": "https://registry.npmmirror.com/rollup/-/rollup-4.60.3.tgz", @@ -2384,6 +2654,26 @@ "fsevents": "~2.3.2" } }, + "node_modules/safe-buffer": { + "version": "5.2.1", + "resolved": "https://registry.npmmirror.com/safe-buffer/-/safe-buffer-5.2.1.tgz", + "integrity": "sha512-rp3So07KcdmmKbGvgaNxQSJr7bGVSVk5S9Eq1F+ppbRo70+YeaDxkw5Dd8NPN+GD6bjnYm2VuPuCXmpuYvmCXQ==", + "funding": [ + { + "type": "github", + "url": "https://github.com/sponsors/feross" + }, + { + "type": "patreon", + "url": "https://www.patreon.com/feross" + }, + { + "type": "consulting", + "url": "https://feross.org/support" + } + ], + "license": "MIT" + }, "node_modules/scheduler": { "version": "0.27.0", "resolved": "https://registry.npmmirror.com/scheduler/-/scheduler-0.27.0.tgz", @@ -2427,6 +2717,30 @@ "node": ">=8" } }, + "node_modules/smart-buffer": { + "version": "4.2.0", + "resolved": "https://registry.npmmirror.com/smart-buffer/-/smart-buffer-4.2.0.tgz", + "integrity": "sha512-94hK0Hh8rPqQl2xXc3HsaBoOXKV20MToPkcXvwbISWLEs+64sBq5kFgn2kJDHb1Pry9yrP0dxrCI9RRci7RXKg==", + "license": "MIT", + "engines": { + "node": ">= 6.0.0", + "npm": ">= 3.0.0" + } + }, + "node_modules/socks": { + "version": "2.8.9", + "resolved": "https://registry.npmmirror.com/socks/-/socks-2.8.9.tgz", + "integrity": "sha512-LJhUYUvItdQ0LkJTmPeaEObWXAqFyfmP85x0tch/ez9cahmhlBBLbIqDFnvBnUJGagb0JbIQrkBs1wJ+yRYpEw==", + "license": "MIT", + "dependencies": { + "ip-address": "^10.1.1", + "smart-buffer": "^4.2.0" + }, + "engines": { + "node": ">= 10.0.0", + "npm": ">= 3.0.0" + } + }, "node_modules/source-map-js": { "version": "1.2.1", "resolved": "https://registry.npmmirror.com/source-map-js/-/source-map-js-1.2.1.tgz", @@ -2436,6 +2750,15 @@ "node": ">=0.10.0" } }, + "node_modules/split2": { + "version": "4.2.0", + "resolved": "https://registry.npmmirror.com/split2/-/split2-4.2.0.tgz", + "integrity": "sha512-UcjcJOWknrNkF6PLX83qcHM6KHgVKNkV62Y8a5uYDVv9ydGQVwAHMKqHdJje1VTWpljG0WYpCDhrCdAOYH4TWg==", + "license": "ISC", + "engines": { + "node": ">= 10.x" + } + }, "node_modules/stats-gl": { "version": "2.4.2", "resolved": "https://registry.npmmirror.com/stats-gl/-/stats-gl-2.4.2.tgz", @@ -2462,6 +2785,15 @@ "integrity": "sha512-hNKz8phvYLPEcRkeG1rsGmV5ChMjKDAWU7/OJJdDErPBNChQXxCo3WZurGpnWc6gZhAzEPFad1aVgyOANH1sMw==", "license": "MIT" }, + "node_modules/string_decoder": { + "version": "1.3.0", + "resolved": "https://registry.npmmirror.com/string_decoder/-/string_decoder-1.3.0.tgz", + "integrity": "sha512-hkRX8U1WjJFd8LsDJ2yQ/wWWxaopEsABU1XfkM8A+j0+85JAGppt16cr1Whg6KIbb4okU6Mql6BOj+uup/wKeA==", + "license": "MIT", + "dependencies": { + "safe-buffer": "~5.2.0" + } + }, "node_modules/suspend-react": { "version": "0.1.3", "resolved": "https://registry.npmmirror.com/suspend-react/-/suspend-react-0.1.3.tgz", @@ -2627,6 +2959,18 @@ } } }, + "node_modules/typedarray": { + "version": "0.0.6", + "resolved": "https://registry.npmmirror.com/typedarray/-/typedarray-0.0.6.tgz", + "integrity": "sha512-/aCDEGatGvZ2BIk+HmLf4ifCJFwvKFNb9/JeZPMulfgFracn9QFcAf5GO8B/mweUjSoblS5In0cWhqpfs/5PQA==", + "license": "MIT" + }, + "node_modules/undici-types": { + "version": "8.3.0", + "resolved": "https://registry.npmmirror.com/undici-types/-/undici-types-8.3.0.tgz", + "integrity": "sha512-j375ScV60dom+YkPFIfTLcOiPxkN/buHz5GobjLhixFuANaNs3C9l4GmrWqejgXWJ7BbJcFYpTEUkS1Ge8bpZQ==", + "license": "MIT" + }, "node_modules/update-browserslist-db": { "version": "1.2.3", "resolved": "https://registry.npmmirror.com/update-browserslist-db/-/update-browserslist-db-1.2.3.tgz", @@ -2667,6 +3011,12 @@ "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0" } }, + "node_modules/util-deprecate": { + "version": "1.0.2", + "resolved": "https://registry.npmmirror.com/util-deprecate/-/util-deprecate-1.0.2.tgz", + "integrity": "sha512-EPD5q1uXyFxJpCrLnCc1nHnq3gOa6DZBocAIiI2TaSCA7VCJ1UJDMagCzIkXNsUYfD1daK//LTEQ8xiIbrHtcw==", + "license": "MIT" + }, "node_modules/utility-types": { "version": "3.11.0", "resolved": "https://registry.npmmirror.com/utility-types/-/utility-types-3.11.0.tgz", @@ -2785,6 +3135,74 @@ "node": ">= 8" } }, + "node_modules/worker-factory": { + "version": "7.0.50", + "resolved": "https://registry.npmmirror.com/worker-factory/-/worker-factory-7.0.50.tgz", + "integrity": "sha512-hhwc0G+sFwM4qBuhJIUBn2p1Jf8v/FwmLUANBf/Q+Lt2uI8mfIZQhXaZQACodQD4R7Zp6cn/6702bIvNn2puJQ==", + "license": "MIT", + "dependencies": { + "@babel/runtime": "^7.29.7", + "fast-unique-numbers": "^9.0.27", + "tslib": "^2.8.1" + } + }, + "node_modules/worker-timers": { + "version": "8.0.34", + "resolved": "https://registry.npmmirror.com/worker-timers/-/worker-timers-8.0.34.tgz", + "integrity": "sha512-WXL+Dqsm0G6dnC66rQsvM3tPT2adhbqSirWUCZGglkALOr8ocS0KlpU0iuKbjflJOlu3ydZikMEVrYnHOM9suw==", + "license": "MIT", + "dependencies": { + "@babel/runtime": "^7.29.7", + "tslib": "^2.8.1", + "worker-timers-broker": "^8.0.18", + "worker-timers-worker": "^9.0.15" + } + }, + "node_modules/worker-timers-broker": { + "version": "8.0.18", + "resolved": "https://registry.npmmirror.com/worker-timers-broker/-/worker-timers-broker-8.0.18.tgz", + "integrity": "sha512-FrjzDVX1wKfZN0gRbCFqv8VHuTncG4sbI/WGEg4tSSQeIsnwqg4YBYWMAHYLJtUDEYYmiK65UKFrVMVk2irDSg==", + "license": "MIT", + "dependencies": { + "@babel/runtime": "^7.29.7", + "broker-factory": "^3.1.15", + "fast-unique-numbers": "^9.0.27", + "tslib": "^2.8.1", + "worker-timers-worker": "^9.0.15" + } + }, + "node_modules/worker-timers-worker": { + "version": "9.0.15", + "resolved": "https://registry.npmmirror.com/worker-timers-worker/-/worker-timers-worker-9.0.15.tgz", + "integrity": "sha512-KKUe7lZ/Aignr51H6hOUik8LwTnIgojH/1lwhli8A8qIEIyewogZTpNpMW5B6BF7nmwBOkUoTYgf1H3QShcjSA==", + "license": "MIT", + "dependencies": { + "@babel/runtime": "^7.29.7", + "tslib": "^2.8.1", + "worker-factory": "^7.0.50" + } + }, + "node_modules/ws": { + "version": "8.21.3", + "resolved": "https://registry.npmmirror.com/ws/-/ws-8.21.3.tgz", + "integrity": "sha512-201TZ/kPWxoPr/OKWjquZR1SWKXcvxdH+e1xrx89b3YbmzLMFCLfnaG1HFIgWzJOEWZ7MvpK++odZufgYR50Rw==", + "license": "MIT", + "engines": { + "node": ">=10.0.0" + }, + "peerDependencies": { + "bufferutil": "^4.0.1", + "utf-8-validate": ">=5.0.2" + }, + "peerDependenciesMeta": { + "bufferutil": { + "optional": true + }, + "utf-8-validate": { + "optional": true + } + } + }, "node_modules/yallist": { "version": "3.1.1", "resolved": "https://registry.npmmirror.com/yallist/-/yallist-3.1.1.tgz", diff --git a/package.json b/package.json index 8f4cf3b..6f2deee 100644 --- a/package.json +++ b/package.json @@ -18,6 +18,7 @@ "@tauri-apps/api": "^2", "@tauri-apps/plugin-autostart": "^2.5.1", "@tauri-apps/plugin-opener": "^2", + "mqtt": "^5.15.2", "react": "^19.1.0", "react-dom": "^19.1.0", "react-router-dom": "^7.15.0", diff --git a/src-tauri/src/lib.rs b/src-tauri/src/lib.rs index 8bb6444..afe553f 100644 --- a/src-tauri/src/lib.rs +++ b/src-tauri/src/lib.rs @@ -3,7 +3,6 @@ mod models; mod server; mod storage; -use std::io::{Read, Write}; use std::time::Duration; #[cfg_attr(mobile, tauri::mobile_entry_point)] @@ -13,32 +12,8 @@ pub fn run() { server::setup_npc(); }); - // 在后台线程启动 HTTP 服务器 - std::thread::spawn(|| { - let rt = tokio::runtime::Runtime::new().expect("无法创建 tokio runtime"); - rt.block_on(async { - server::start().await; - }); - }); - - // 等待 HTTP 服务器就绪后再打开窗口 - for i in 0..50 { - if let Ok(mut s) = std::net::TcpStream::connect_timeout( - &"0.0.0.0:10801".parse().unwrap(), - Duration::from_millis(500), - ) { - // 发送一个简单的 HTTP 请求测试 - let _ = s.write_all(b"GET /api/state HTTP/1.0\r\n\r\n"); - let mut buf = [0u8; 4]; - if s.read(&mut buf).is_ok() { - break; - } - } - if i == 0 { - eprintln!("[dpm] 等待 HTTP 服务器启动..."); - } - std::thread::sleep(Duration::from_millis(100)); - } + // 等待内网穿透就绪（可选，不阻塞） + std::thread::sleep(Duration::from_millis(200)); tauri::Builder::default() .plugin(tauri_plugin_opener::init()) diff --git a/src/components/AiChatPanel.jsx b/src/components/AiChatPanel.jsx index 6da4de1..bf7e1f1 100644 --- a/src/components/AiChatPanel.jsx +++ b/src/components/AiChatPanel.jsx @@ -1,241 +1,214 @@ import { useState, useRef, useEffect, useCallback } from 'react'; import Icon from './Icons'; +import { API_BASE } from '../config'; +import { getMqttStatus } from '../utils/mqtt'; /* ========================================================= - AI 智能助手对话面板（共享）—— 遵循 bd- 浅色科技 UI 规范 - 两种交互模式： - · 文字对话：消息流 + 快捷提问 + 输入发送 - · 语音对话：语音交互按钮（聆听 → 识别 → 以文字进入对话流） + AI 智能助手对话面板 —— 文字 / 语音双模式 + · 文字：后端 /api/ai/chat（阿里云通义千问 + 工具调用） + · 语音：本地录音 → 后端 /api/ai/asr（阿里云 paraformer）→ 进入对话流 + 后端不可用时自动回退本地模拟（离线兜底） ========================================================= */ -/* ---------- 快捷提问 ---------- */ const QUICK_QUESTIONS = [ '如何申请入驻园区？', '园区有哪些政策扶持？', - '办公场地怎么收费？', + '展示入驻企业卡片', 'AI 赋能服务有哪些？', - '三个分区有什么区别？', + '切换到数字孪生页面', ]; -/* 语音识别兜底题库（无麦克风权限 / 环境不支持时模拟识别） */ -const VOICE_SAMPLES = [ - '如何申请入驻园区？', - '园区有哪些政策扶持？', - '办公场地怎么收费？', - 'AI 赋能服务有哪些？', - '三个分区有什么区别？', - '园区有哪些入驻企业？', - '怎么联系创业导师？', +/* 离线兜底回复（后端不可用时） */ +const FALLBACK_REPLIES = [ + '园区提供「空间 + 孵化 + 融资 + 政策 + 资源 + AI 赋能 + 综合服务」七位一体服务，在园项目 158 家，累计带动就业 2,186 人，累计营收 2.08 亿元。', + '入驻流程：提交申请 → 项目评审 → 签订协议 → 安排场地并对接导师服务。在园项目 158 家，累计孵化 208 余家。', + '园区政策覆盖场地租金减免、创业补贴、税费优惠与高企认定申报辅导（在园高企 32 家）。', + '园区按成长阶段分三个区域：加速区（A1–A12）、国际区（I1–I7）、成长区（G1–G8），共 39 家入驻企业。', ]; +const pick = (arr) => arr[Math.floor(Math.random() * arr.length)]; -/* ---------- 园区知识库（模拟回复） ---------- */ -const WELCOME = '您好，我是 OPC 园区 AI 智能助手。\n\n我可以为您解答入驻流程、政策扶持、场地服务、AI 赋能、企业名录等问题。您可以在「文字」模式输入问题，或切换到「语音」模式直接说话提问。'; - -const RULES = [ - { - match: /入驻|申请|入孵|入园|如何加入|怎样加入/, - reply: '入驻流程如下：\n\n1. 提交入驻申请（线上表单或到园区服务中心现场办理）\n2. 项目评审（园区组织专家对项目可行性、团队背景进行评估）\n3. 签订入驻协议，办理入驻手续\n4. 安排办公场地，对接创业导师与孵化服务\n\n目前园区在园项目 158 家，累计孵化企业 208 余家。如需协助，可直接联系园区服务中心。', - }, - { - match: /政策|补贴|优惠|扶持|减免|奖励|资助/, - reply: '园区政策服务覆盖「七位一体」中的政策维度：\n\n· 场地租金减免：符合条件的大学生创业项目可享受场地优惠\n· 创业补贴：协助对接省、市两级创业补贴与一次性创业资助\n· 税费优惠：对接小微企业所得税减免、增值税优惠等政策\n· 项目申报：指导高企认定（目前在园高新技术企业 32 家）、科技型中小企业备案\n\n更多政策细节可咨询园区政策服务窗口。', - }, - { - match: /场地|办公室|工位|租金|收费|面积|多少钱|价格/, - reply: '园区总建筑面积 1.2 万㎡，按功能划分为三个区域：\n\n· 加速区（A1–A12）：成长型项目办公室，共 11 间独立办公室 + 1 间园区管理办公室\n· 国际区（I1–I7）：面向国际合作的办公空间（7 间）\n· 成长区（G1–G8）：初创团队成长空间（8 间）\n\n租金按创业项目阶段与政策给予差异化优惠，具体可到园区服务中心咨询，或询问「入驻流程」。', - }, - { - match: /AI|模型|算力|tokens|token|工具|智能|赋能|大模型/, - reply: '园区 AI 赋能服务是「七位一体」的核心特色：\n\n· 大模型推理：接入 DeepSeek-V3、通义千问、智谱 GLM-4、豆包、讯飞星火等多模型\n· 工具调用：文档生成、数据查询、图像创作、代码执行、语音合成等智能工具\n· 算力与成本：实时提供 token 消耗统计与速率监控，帮助企业控制 AI 使用成本\n\n今日园区 AI 推理任务持续运行，多模型负载均衡调度，服务节点 12/12 在线。', - }, - { - match: /加速区|国际区|成长区|分区|区域|区别|布局/, - reply: '园区按企业成长阶段划分三个区域：\n\n· 加速区（蓝色）：面向已具备产品与市场验证的成长型项目，提供独立办公室（A1–A12），目前在驻 9 家企业\n· 国际区（青色）：面向国际合作与跨境业务项目（I1–I7），在驻 7 家\n· 成长区（绿色）：面向初创团队的共享成长空间（G1–G8），在驻 8 家\n\n园区管理办公室位于加速区 M 房间，提供一站式服务。', - }, - { - match: /企业|公司|名录|名单|入驻企业|有哪些企业|查.*企业/, - reply: '园区目前有 39 家入驻企业，分布在三个区域：\n\n· 加速区：云南派音人工智能科技、米勒克尔蓝宝石珠宝、云南宸中低空经济等 9 家\n· 国际区：仰光客厅、中越生物医疗、酷享野农AI农业等 7 家\n· 成长区：Facebook越南跨境电商、昆明云韵体育、云南星瑞航空等 8 家\n\n您也可以直接查看右侧「企业分布」面板，按分区浏览企业名录与房间号。', - }, - { - match: /融资|投资|资金|贷款|估值|资本/, - reply: '园区融资服务包含：\n\n· 融资对接：定期组织路演与投资机构对接活动\n· 孵化估值：累计孵化企业估值约 5.2 亿元\n· 金融支持：协助对接银行创业贷款、政府创业担保贷款\n· 财务辅导：提供融资方案设计与商业计划书辅导\n\n有融资需求的企业可向园区服务中心提交商业计划书。', - }, - { - match: /就业|招聘|岗位|人才|用工/, - reply: '园区累计带动就业 2,186 人（其中高校毕业生 1,680 人，实习岗位 506 个）。\n\n· 企业招聘：在驻企业持续发布岗位（今日新增多个岗位）\n· 人才对接：与在昆高校共建实习实训基地\n· 创业带动：园区鼓励以创业带动就业，多个项目已形成稳定用工\n\n具体招聘岗位可关注园区实时动态与入驻企业名录。', - }, - { - match: /导师|培训|课程|辅导|孵化服务|孵化器/, - reply: '园区配备创业导师 58 位，提供全周期孵化服务：\n\n· 一对一辅导：创业导师定期坐诊，覆盖商业模式、法律财税、市场营销\n· 培训课程：创业训练营、行业专题沙龙、政策解读会\n· 资源对接：技术、供应链、渠道等产业资源链接\n· 公共服务：工商注册、知识产权、法律咨询一站式代办', - }, - { - match: /你好|您好|hi|hello|嗨|在吗/, - reply: '您好！我是 OPC 园区 AI 智能助手。\n\n可以问我：入驻流程、政策扶持、场地收费、AI 赋能、企业名录、融资服务等问题，也可以切换到「语音」模式直接说话提问。', - }, - { - match: /谢谢|感谢|好的|明白|ok/, - reply: '不客气，随时为您服务。您也可以点击右侧「企业分布」查看入驻企业，或继续向我提问。', - }, -]; - -const DEFAULT_REPLY = '园区提供「空间 + 孵化 + 融资 + 政策 + 资源 + AI 赋能 + 综合服务」七位一体服务，在园项目 158 家，累计带动就业 2,186 人，累计营收 2.08 亿元。\n\n您可以这样问我：\n· 如何申请入驻园区？\n· 园区有哪些政策扶持？\n· AI 赋能服务有哪些？'; - -function getReply(input) { - const text = String(input || '').trim(); - for (const rule of RULES) { - if (rule.match.test(text)) return rule.reply; - } - return DEFAULT_REPLY; -} +/* 本地兜底识别题库（ASR 不可用时） */ +const VOICE_SAMPLES = QUICK_QUESTIONS; /* ---------- 消息 ---------- */ let msgId = 0; const nextId = () => ++msgId; -const pick = (arr) => arr[Math.floor(Math.random() * arr.length)]; + +/** 执行后端返回的工具调用。 + 后端已通过 MQTT 广播（发布成功时所有大屏都会收到，本地跳过避免重复）； + 仅当 MQTT 发布失败 / 后端不可达时本地执行，保证当前屏幕也能响应 */ +function executeLocalTools(tools, mqttPublished) { + if (!Array.isArray(tools) || tools.length === 0) return; + if (mqttPublished !== false) return; + for (const tool of tools) { + const type = tool.type; + const params = tool.params || {}; + if (type === 'navigate' || type === 'control' || type === 'alert' || type === 'show_card') { + window.dispatchEvent(new CustomEvent('dpm:mqtt-local', { detail: { action: type, params } })); + } + } +} export default function AiChatPanel() { - const [msgs, setMsgs] = useState(() => [ - { id: nextId(), role: 'ai', text: WELCOME }, - ]); + const [msgs, setMsgs] = useState(() => [{ id: nextId(), role: 'ai', text: '您好，我是 OPC 园区 AI 智能助手（阿里云通义千问）。\n\n支持文字与语音提问，可以为您解答入驻流程、政策扶持、场地服务、AI 赋能等问题，还可以通过语音或文字让我切换页面、展示企业卡片。' }]); const [input, setInput] = useState(''); const [typing, setTyping] = useState(false); - const [mode, setMode] = useState('text'); // text | voice - const [voiceState, setVoiceState] = useState('idle'); // idle | listening | processing + const [mode, setMode] = useState('text'); + const [voiceState, setVoiceState] = useState('idle'); // idle | recording | transcribing const scrollRef = useRef(null); const timerRef = useRef(null); - const recRef = useRef(null); + const recorderRef = useRef(null); + const chunksRef = useRef([]); + const voiceStateRef = useRef(voiceState); + + useEffect(() => { voiceStateRef.current = voiceState; }, [voiceState]); - // 新消息 / 状态变化自动滚动到底部 useEffect(() => { const el = scrollRef.current; if (el) el.scrollTop = el.scrollHeight; }, [msgs, typing, mode, voiceState]); - // 卸载清理：定时器 + 语音识别 useEffect(() => { return () => { clearTimeout(timerRef.current); - try { recRef.current && recRef.current.abort && recRef.current.abort(); } catch { /* ignore */ } + if (recorderRef.current && recorderRef.current.state !== 'inactive') { + try { recorderRef.current.stop(); } catch { /* ignore */ } + } }; }, []); - /** 生成用户消息并触发 AI 回复 */ - const send = useCallback((raw, viaVoice = false) => { + /** 发送消息 → 后端 LLM */ + const send = useCallback(async (raw, viaVoice = false) => { const text = String(raw || '').trim(); if (!text || typing) return; setInput(''); setMsgs((prev) => [...prev, { id: nextId(), role: 'me', text, voice: viaVoice }]); setTyping(true); - const reply = getReply(text); - timerRef.current = setTimeout(() => { - setMsgs((prev) => [...prev, { id: nextId(), role: 'ai', text: reply }]); - setTyping(false); - }, 700 + Math.random() * 600); + + let reply = null; + let tools = []; + try { + const res = await fetch(`${API_BASE}/api/ai/chat`, { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ messages: [{ role: 'user', content: text }] }), + }); + if (res.ok) { + const data = await res.json(); + reply = data.reply; + tools = data.tools || []; + } + } catch { /* 后端不可用 */ } + + if (!reply) reply = pick(FALLBACK_REPLIES); + setTyping(false); + setMsgs((prev) => [...prev, { id: nextId(), role: 'ai', text: reply }]); + executeLocalTools(tools); }, [typing]); const clear = useCallback(() => { clearTimeout(timerRef.current); setTyping(false); - setMsgs([{ id: nextId(), role: 'ai', text: WELCOME }]); + setMsgs([{ id: nextId(), role: 'ai', text: '您好，我是 OPC 园区 AI 智能助手。有什么可以帮您？' }]); }, []); - /* ================= 语音对话 ================= */ + /* ================= 语音对话（录音 → 后端 ASR） ================= */ - // 供安全兜底定时器读取当前状态 - const voiceStateRef = useRef(voiceState); - useEffect(() => { voiceStateRef.current = voiceState; }, [voiceState]); - - /** 结束聆听：把识别出的文字送入对话流 */ - const finishVoice = useCallback((text) => { - setVoiceState('processing'); - clearTimeout(timerRef.current); - timerRef.current = setTimeout(() => { - setVoiceState('idle'); - send(text, true); - }, 450); - }, [send]); - - /** 兜底：环境不支持 / 无麦克风时模拟识别 */ - const fallbackVoice = useCallback(() => { - if (recRef.current) { try { recRef.current.abort(); } catch { /* ignore */ } recRef.current = null; } - finishVoice(pick(VOICE_SAMPLES)); - }, [finishVoice]); - - /** 点击语音按钮：idle → 开始聆听；listening → 结束 */ - const toggleVoice = useCallback(() => { - if (voiceState === 'processing') return; - if (voiceState === 'listening') { - // 用户主动结束：尝试取识别结果，无结果则兜底 - clearTimeout(timerRef.current); - if (recRef.current) { - try { recRef.current.stop(); } catch { /* ignore */ } - } - return; // 由 onend/onerror 或兜底定时器完成收尾 + const pickMimeType = () => { + const types = ['audio/mp4', 'audio/webm;codecs=opus', 'audio/ogg;codecs=opus', 'audio/webm']; + for (const t of types) { + if (window.MediaRecorder && MediaRecorder.isTypeSupported(t)) return t; } - // 开始聆听 - setVoiceState('listening'); - const SR = window.SpeechRecognition || window.webkitSpeechRecognition; - if (SR) { - try { - const rec = new SR(); - rec.lang = 'zh-CN'; - rec.interimResults = false; - rec.maxAlternatives = 1; - let done = false; - rec.onresult = (e) => { - if (done) return; - done = true; - clearTimeout(timerRef.current); - const t = Array.from(e.results).map((r) => r[0].transcript).join(' '); - finishVoice(t || pick(VOICE_SAMPLES)); + return ''; + }; + + const startRecording = useCallback(() => { + const mime = pickMimeType(); + if (!window.MediaRecorder || !navigator.mediaDevices?.getUserMedia) { + // 无录音能力：直接模拟 + setVoiceState('transcribing'); + timerRef.current = setTimeout(() => { + setVoiceState('idle'); + send(pick(VOICE_SAMPLES), true); + }, 1200); + return; + } + navigator.mediaDevices.getUserMedia({ audio: true }) + .then((stream) => { + const rec = new MediaRecorder(stream, mime ? { mimeType: mime } : undefined); + chunksRef.current = []; + rec.ondataavailable = (e) => { if (e.data && e.data.size > 0) chunksRef.current.push(e.data); }; + rec.onstop = async () => { + stream.getTracks().forEach((t) => t.stop()); + setVoiceState('transcribing'); + const blob = new Blob(chunksRef.current, { type: mime || 'audio/webm' }); + try { + const fmt = (mime || 'webm').split(';')[0].split('/')[1] || 'm4a'; + const form = new FormData(); + form.append('file', blob, `recording.${fmt === 'mp4' ? 'm4a' : fmt}`); + form.append('format', fmt === 'mp4' ? 'm4a' : fmt); + const res = await fetch(`${API_BASE}/api/ai/asr`, { method: 'POST', body: form }); + const data = await res.json(); + const text = (data && data.text || '').trim(); + if (text) { + send(text, true); + } else { + setVoiceState('idle'); + setMsgs((prev) => [...prev, { id: nextId(), role: 'ai', text: '抱歉，没有听清您的问题，请再试一次，或改用文字输入。' }]); + } + } catch { + // 后端不可用：回退本地模拟识别 + setVoiceState('transcribing'); + timerRef.current = setTimeout(() => { + setVoiceState('idle'); + send(pick(VOICE_SAMPLES), true); + }, 1000); + } }; rec.onerror = () => { - if (done) return; - done = true; - clearTimeout(timerRef.current); - fallbackVoice(); + stream.getTracks().forEach((t) => t.stop()); + setVoiceState('idle'); + send(pick(VOICE_SAMPLES), true); }; - rec.onend = () => { - recRef.current = null; - if (!done) { - done = true; - clearTimeout(timerRef.current); - fallbackVoice(); - } - }; - recRef.current = rec; + recorderRef.current = rec; rec.start(); - // 安全兜底：4 秒内无结果则模拟（识别静默失败的环境） + setVoiceState('recording'); + }) + .catch(() => { + // 麦克风权限被拒：模拟 + setVoiceState('transcribing'); timerRef.current = setTimeout(() => { - if (!done && voiceStateRef.current === 'listening') { - done = true; - try { rec.abort(); } catch { /* ignore */ } - fallbackVoice(); - } - }, 4000); - return; - } catch { /* 继续走兜底 */ } - } - // 无 SpeechRecognition：模拟聆听 → 识别 - timerRef.current = setTimeout(() => { - fallbackVoice(); - }, 1300); - }, [voiceState, finishVoice, fallbackVoice]); + setVoiceState('idle'); + send(pick(VOICE_SAMPLES), true); + }, 1200); + }); + }, [send]); + + const toggleVoice = useCallback(() => { + if (voiceStateRef.current === 'recording') { + const rec = recorderRef.current; + if (rec && rec.state === 'recording') { + rec.stop(); // 触发 onstop → 上传识别 + } else { + setVoiceState('idle'); + } + } else if (voiceStateRef.current === 'idle') { + startRecording(); + } + }, [startRecording]); - // 切换模式时中止聆听 const switchMode = useCallback((m) => { setMode(m); - if (voiceState === 'listening') { - clearTimeout(timerRef.current); - if (recRef.current) { try { recRef.current.abort(); } catch { /* ignore */ } recRef.current = null; } + if (voiceStateRef.current === 'recording') { + try { recorderRef.current && recorderRef.current.stop(); } catch { /* ignore */ } setVoiceState('idle'); } - }, [voiceState]); + }, []); const voiceHint = { idle: '点击麦克风，说出你的问题', - listening: '正在聆听… 请说出你的问题', - processing: '正在识别语音…', + recording: '正在聆听… 再次点击结束', + transcribing: '正在识别语音…', }[voiceState]; return ( @@ -245,41 +218,29 @@ export default function AiChatPanel() {
AI 智能助手 - OPC 园区知识库 · 文字 / 语音双模式 + 阿里云通义千问 · 语音识别
- -
- DeepSeek-V3 + 通义千问 - {/* 消息区（文字 / 语音共用） */} + {/* 消息区 */}
{msgs.map((m) => (
- {m.role === 'ai' && ( - - )} + {m.role === 'ai' && }
- {m.voice && ( - 语音 - )} + {m.voice && 语音} {m.text}
@@ -292,7 +253,7 @@ export default function AiChatPanel() { )}
- {/* 文字模式：快捷提问 + 输入区 */} + {/* 文字模式 */} {mode === 'text' && ( <>
@@ -306,7 +267,7 @@ export default function AiChatPanel() {
setInput(e.target.value)} onKeyDown={(e) => { if (e.key === 'Enter' && !e.nativeEvent.isComposing) { @@ -315,39 +276,34 @@ export default function AiChatPanel() { } }} /> -
)} - {/* 语音模式：语音交互按钮 */} + {/* 语音模式 */} {mode === 'voice' && (
- {voiceState === 'listening' && } + {voiceState === 'recording' && } {voiceHint}
- {voiceState === 'listening' ? '再次点击结束并发送' : '点击开始说话 · 再次点击结束'} + {voiceState === 'recording' ? '再次点击结束并识别' : '点击开始说话 · 阿里云语音识别'}
)} diff --git a/src/components/DpmOverlays.jsx b/src/components/DpmOverlays.jsx new file mode 100644 index 0000000..9768c3a --- /dev/null +++ b/src/components/DpmOverlays.jsx @@ -0,0 +1,160 @@ +import { useState, useEffect, useCallback, useRef } from 'react'; +import Icon from './Icons'; +import { API_BASE } from '../config'; + +/* ========================================================= + DpmOverlays —— 后端/AI 指令驱动的全局覆盖层 + · alert → 右上角通知（自动消失） + · show_card → 中央信息卡片（企业分布 / 分区 / 园区总览 / 自定义） + 遵循 bd- 浅色科技 UI 规范，图标全部使用 appica SVG + ========================================================= */ + +function CardContent({ card }) { + const [data, setData] = useState(null); + const { card: type, title, content } = card || {}; + + useEffect(() => { + let alive = true; + if (type === 'companies') { + fetch(`${API_BASE}/api/park/companies`) + .then((r) => r.json()) + .then((d) => alive && setData(d.companies || [])) + .catch(() => alive && setData([])); + } else if (type === 'zones') { + fetch(`${API_BASE}/api/park/zones`) + .then((r) => r.json()) + .then((d) => alive && setData(d.zones || [])) + .catch(() => alive && setData([])); + } else if (type === 'overview') { + fetch(`${API_BASE}/api/dashboard/snapshot`) + .then((r) => r.json()) + .then((d) => alive && setData(d)) + .catch(() => alive && setData(null)); + } + return () => { alive = false; }; + }, [type]); + + if (type === 'companies') { + const groups = {}; + (data || []).forEach((c) => { + (groups[c.zone] = groups[c.zone] || []).push(c); + }); + return ( +
+ {Object.keys(groups).map((z) => ( +
+
{z}
+
+ {groups[z].map((c) => ( + + {c.room} + {c.name} + + ))} +
+
+ ))} +
+ ); + } + + if (type === 'zones') { + return ( +
+
+ {(data || []).map((z) => ( + + {z.name} + {z.count} 家 + + ))} +
+
+ ); + } + + if (type === 'overview' && data) { + const rows = [ + ['在园项目', `${data.projects?.inPark ?? '-'} 家`], + ['累计孵化', `${data.projects?.cum ?? '-'} 家`], + ['带动就业', `${(data.jobs?.total ?? 0).toLocaleString()} 人`], + ['累计营收', `${(data.revenue?.total ?? 0) / 10000} 亿`], + ['今日营收', `${data.revenue?.today ?? '-'} 万`], + ['工具调用', `${(data.tools?.today ?? 0).toLocaleString()} 次`], + ['AI 速率', `${data.token?.rate ?? '-'} t/s`], + ['设备在线', `${data.park?.devices ?? '-'}%`], + ]; + return ( +
+ {rows.map(([k, v]) => ( +
+ {k} + {v} +
+ ))} +
+ ); + } + + // custom / 未知类型：标题 + 内容 + return ( +
+
{content || '（无内容）'}
+
+ ); +} + +export default function DpmOverlays() { + const [alert, setAlert] = useState(null); // {title, content, id} + const [card, setCard] = useState(null); // {card, title, content, id} + const alertTimer = useRef(null); + + const showAlert = useCallback((params) => { + const item = { title: params.title || '提示', content: params.content || '', id: Date.now() + Math.random() }; + setAlert(item); + clearTimeout(alertTimer.current); + alertTimer.current = setTimeout(() => setAlert(null), 6000); + }, []); + + const showCard = useCallback((params) => { + setCard({ card: params.card || 'custom', title: params.title || '', content: params.content || '', id: Date.now() + Math.random() }); + }, []); + + useEffect(() => { + const onAlert = (e) => showAlert(e.detail || {}); + const onCard = (e) => showCard(e.detail || {}); + window.addEventListener('dpm:alert', onAlert); + window.addEventListener('dpm:show-card', onCard); + return () => { + window.removeEventListener('dpm:alert', onAlert); + window.removeEventListener('dpm:show-card', onCard); + }; + }, [showAlert, showCard]); + + return ( + <> + {alert && ( +
+
+
+ {alert.title} + {alert.content && {alert.content}} +
+ +
+ )} + {card && ( +
setCard(null)}> +
e.stopPropagation()}> +
+ + {card.title || 'AI 助手卡片'} + +
+ +
+
+ )} + + ); +} diff --git a/src/components/ParkOverviewStrip.jsx b/src/components/ParkOverviewStrip.jsx index e7545c1..f62deec 100644 --- a/src/components/ParkOverviewStrip.jsx +++ b/src/components/ParkOverviewStrip.jsx @@ -20,7 +20,10 @@ export default function ParkOverviewStrip({ d }) { ]; return (