From 83bf19a3e54b4d865a4d37adf243dc3c567100f6 Mon Sep 17 00:00:00 2001 From: Pine Date: Tue, 18 Aug 2026 02:06:07 +0800 Subject: [PATCH] =?UTF-8?q?feat(agent):=20=E6=99=BA=E8=83=BD=E4=BD=93?= =?UTF-8?q?=E6=8E=A5=E5=85=A5=E5=B7=A5=E5=85=B7=E8=B0=83=E7=94=A8=20+=20?= =?UTF-8?q?=E5=9B=AD=E5=8C=BA=E7=9F=A5=E8=AF=86=E5=BA=93=EF=BC=88RAG?= =?UTF-8?q?=EF=BC=89?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 后端： - tools.py：工具注册表（get_park_overview 园区实时数据 / query_companies 企业名录 / control_display 大屏控制 / get_time），POST /api/tools/exec 执行 - rag.py：园区知识库（park.md 分块 → dashscope text-embedding-v3 → numpy 余弦检索），/api/kb/brief 摘要注入 + /api/kb/retrieve 动态检索 - 知识索引 kb_index.json 入库，部署免首次构建 前端（VoiceAssistant）： - TOOL_DEFS 经 session.update 传给 LLM；toolcall 事件 → 后端执行 → sendToolOutput + requestResponse - instructions 拼接园区知识摘要；工具调用气泡提示 - 测试通过：4 个工具，检索「入驻政策」正确命中政策段落 --- backend/app/rag.py | 102 +++++++++++++++++++++++++ backend/app/routers.py | 39 ++++++++++ backend/app/tools.py | 127 ++++++++++++++++++++++++++++++++ backend/knowledge/kb_index.json | 1 + backend/knowledge/park.md | 31 ++++++++ src/pages/VoiceAssistant.jsx | 76 ++++++++++++++++++- 6 files changed, 372 insertions(+), 4 deletions(-) create mode 100644 backend/app/rag.py create mode 100644 backend/app/tools.py create mode 100644 backend/knowledge/kb_index.json create mode 100644 backend/knowledge/park.md diff --git a/backend/app/rag.py b/backend/app/rag.py new file mode 100644 index 0000000..815920b --- /dev/null +++ b/backend/app/rag.py @@ -0,0 +1,102 @@ +# -*- coding: utf-8 -*- +"""园区知识库 —— 轻量本地 RAG（embedding + numpy 余弦检索） + +- 知识源：backend/knowledge/park.md（按标题/段落分块） +- 向量化：dashscope text-embedding-v3（云端 API，索引构建一次后缓存） +- 检索：numpy 余弦 top-k（资料量小，暴力检索足够） +- 提供： + - retrieve(query, top_k) → 相关段落（供对话动态注入） + - brief() → 固定知识摘要（供前端拼进 instructions，静态知识一次注入） +""" +import json +import logging +import os +from pathlib import Path + +import numpy as np + +log = logging.getLogger("dpm.rag") + +KB_FILE = Path(__file__).resolve().parent.parent / "knowledge" / "park.md" +INDEX_FILE = Path(__file__).resolve().parent.parent / "knowledge" / "kb_index.json" +EMBED_MODEL = "text-embedding-v3" + +_index = None # 缓存 {chunks, embeddings} + + +def _chunk_md(text: str) -> list[str]: + """按标题/段落分块""" + chunks: list[str] = [] + cur: list[str] = [] + for line in text.splitlines(): + if line.startswith("#"): + if cur: + chunks.append("\n".join(cur).strip()) + cur = [line] + else: + cur.append(line) + if cur: + chunks.append("\n".join(cur).strip()) + return [c for c in chunks if len(c) > 10] + + +def _embed(texts: list[str]) -> list[list[float]]: + """dashscope text-embedding-v3 批量向量化""" + import dashscope + + api_key = os.environ.get("DASHSCOPE_API_KEY") or "" + resp = dashscope.TextEmbedding.call( + model=EMBED_MODEL, + input=texts, + api_key=api_key, + ) + if resp.status_code != 200: + raise RuntimeError(f"embedding API {resp.status_code}: {resp.code} {resp.message}") + out = [e["embedding"] for e in resp.output["embeddings"]] + return out + + +def _load_index(): + """懒加载索引；缺失时构建并缓存""" + global _index + if _index is not None: + return _index + if INDEX_FILE.exists(): + try: + _index = json.loads(INDEX_FILE.read_text("utf-8")) + log.info("rag: 知识索引已加载（%d 块）", len(_index["chunks"])) + return _index + except Exception: # noqa: BLE001 + log.warning("rag: 索引损坏，重建") + # 构建 + chunks = _chunk_md(KB_FILE.read_text("utf-8")) + log.info("rag: 构建知识索引（%d 块，embedding 中…）", len(chunks)) + embs = _embed(chunks) + _index = {"chunks": chunks, "embeddings": embs} + INDEX_FILE.write_text(json.dumps(_index, ensure_ascii=False), "utf-8") + log.info("rag: 知识索引构建完成 -> %s", INDEX_FILE) + return _index + + +def retrieve(query: str, top_k: int = 3) -> list[str]: + """检索与 query 最相关的知识段落""" + if not query or not query.strip(): + return [] + idx = _load_index() + q = _embed([query])[0] + sims = np.dot(np.array(idx["embeddings"]), np.array(q)) + top = np.argsort(-sims)[:top_k] + return [idx["chunks"][int(i)] for i in top if float(sims[int(i)]) > 0.3] + + +def brief(max_chars: int = 1200) -> str: + """固定知识摘要（前端拼进 instructions，静态知识一次注入）""" + idx = _load_index() + out = [] + total = 0 + for c in idx["chunks"]: + if total + len(c) > max_chars: + break + out.append(c) + total += len(c) + return "\n\n".join(out) diff --git a/backend/app/routers.py b/backend/app/routers.py index edd4ccb..c34e33e 100644 --- a/backend/app/routers.py +++ b/backend/app/routers.py @@ -426,3 +426,42 @@ def vision_frame(body: VisionFrameBody): return {"ok": False, "error": "missing image"} from .vision_yolo import predict_base64 return predict_base64(img_b64) + + +# ==================== 智能体工具调用 + 知识库 ==================== +class ToolsExecBody(BaseModel): + name: str = "" + args: dict = {} + +@router.post("/api/tools/exec") +def tools_exec(body: ToolsExecBody): + """执行智能体工具（LLM function calling）：name + args → 结果字符串""" + name = (body.name or "").strip() + if not name: + return {"ok": False, "error": "missing tool name"} + from .tools import exec_tool + result = exec_tool(name, body.args or {}) + return {"ok": True, "result": result} + +@router.get("/api/kb/brief") +def kb_brief(max_chars: int = 1200): + """园区知识摘要（前端拼进对话 instructions）""" + try: + from .rag import brief + return {"ok": True, "brief": brief(max_chars=max_chars)} + except Exception as e: # noqa: BLE001 + log.warning("kb brief 失败: %s", e) + return {"ok": False, "error": str(e)} + +@router.get("/api/kb/retrieve") +def kb_retrieve(q: str = "", top_k: int = 3): + """知识库检索（query → 相关段落）""" + if not q.strip(): + return {"ok": False, "error": "missing q"} + try: + from .rag import retrieve + chunks = retrieve(q, top_k=top_k) + return {"ok": True, "chunks": chunks} + except Exception as e: # noqa: BLE001 + log.warning("kb retrieve 失败: %s", e) + return {"ok": False, "error": str(e)} diff --git a/backend/app/tools.py b/backend/app/tools.py new file mode 100644 index 0000000..1b40e1c --- /dev/null +++ b/backend/app/tools.py @@ -0,0 +1,127 @@ +# -*- coding: utf-8 -*- +"""智能体工具注册表 —— LLM function calling 的后端执行器 + +- TOOLS：工具名 → 描述 + JSON Schema 参数（给 LLM 声明用） +- exec_tool(name, args)：执行工具，返回给 LLM 的字符串结果（JSON） +- 供 POST /api/tools/exec 调用；前端 s2s 客户端收到 toolcall 事件后转发到此执行 +""" +import json +import logging +from datetime import datetime + +log = logging.getLogger("dpm.tools") + + +# ── 工具实现 ──────────────────────────────────────────────────────────── + +def _get_park_overview(args): + """园区实时概览（在园项目/就业/营收/在园人数等）""" + from .sim_engine import sim_engine + d = sim_engine.snapshot() + return json.dumps({ + "在园项目": d["projects"]["inPark"], + "累计孵化企业": d["projects"]["cum"], + "今日新增项目": d["projects"]["todayNew"], + "带动就业(人)": d["jobs"]["total"], + "今日新增就业": d["jobs"]["todayNew"], + "累计营收(万元)": d["revenue"]["total"], + "今日营收(万元)": d["revenue"]["today"], + "营收同比增速(%)": d["revenue"]["growth"], + "设备在线率(%)": d["park"]["devices"], + "今日能耗(kWh)": d["park"]["energy"], + "当前在园人数": d["park"]["people"], + "会议预约": d["park"]["meeting"], + "工位使用": d["park"]["desk"], + }, ensure_ascii=False) + + +def _query_companies(args): + """园区入驻企业名录查询（关键词过滤）""" + from .sim_engine import COMPANY_NAMES + q = (args.get("keyword") or "").strip() + names = [n for n in COMPANY_NAMES if q in n] if q else list(COMPANY_NAMES) + return json.dumps({ + "total": len(names), + "keyword": q, + "companies": names[:20], + }, ensure_ascii=False) + + +def _control_display(args): + """大屏显示控制：切页 / 弹通知 / 媒体播放暂停（经 MQTT 广播到大屏）""" + from .mqtt import hub + action = (args.get("action") or "").strip() + target = (args.get("target") or "").strip() + if action not in ("switch_page", "alert", "media_play", "media_pause"): + return json.dumps({"error": f"不支持的 action: {action}"}, ensure_ascii=False) + params = {"target": target} if target else {} + ok = hub.publish_command(action, params).get("published", False) + return json.dumps({"ok": ok, "action": action, "target": target}, ensure_ascii=False) + + +def _get_time(args): + """当前日期时间""" + return json.dumps({"datetime": datetime.now().strftime("%Y-%m-%d %H:%M:%S")}, ensure_ascii=False) + + +# ── 注册表 ────────────────────────────────────────────────────────────── + +TOOLS = { + "get_park_overview": { + "fn": _get_park_overview, + "description": "获取园区实时运营概览：在园项目数、累计孵化企业、带动就业、营收（今日/累计）、设备在线率、在园人数、能耗等。回答园区数据类问题时使用。", + "parameters": {"type": "object", "properties": {}}, + }, + "query_companies": { + "fn": _query_companies, + "description": "查询园区入驻企业名录，支持按企业名关键词过滤。回答'有哪些企业/某企业是否入驻'时使用。", + "parameters": { + "type": "object", + "properties": {"keyword": {"type": "string", "description": "企业名关键词，可为空字符串"}}, + }, + }, + "control_display": { + "fn": _control_display, + "description": "控制大屏显示：switch_page 切换页面、alert 弹通知、media_play/media_pause 控制媒体播放。用户要求控制大屏时使用。", + "parameters": { + "type": "object", + "properties": { + "action": {"type": "string", "enum": ["switch_page", "alert", "media_play", "media_pause"]}, + "target": {"type": "string", "description": "目标：页面路径（如 /、/twin、/ai、/voice）或通知文本"}, + }, + }, + }, + "get_time": { + "fn": _get_time, + "description": "获取当前日期时间。用户问'现在几点/今天几号'时使用。", + "parameters": {"type": "object", "properties": {}}, + }, +} + + +def tool_schemas(): + """给 LLM 的 tools 定义（OpenAI function calling 格式）""" + return [ + { + "type": "function", + "name": name, + "description": t["description"], + "parameters": t["parameters"], + } + for name, t in TOOLS.items() + ] + + +def exec_tool(name: str, args: dict): + """执行工具 → 返回给 LLM 的字符串结果（JSON）""" + t = TOOLS.get(name) + if not t: + log.warning("tools: 未知工具 %s", name) + return json.dumps({"error": f"未知工具: {name}"}, ensure_ascii=False) + try: + result = t["fn"](args or {}) + log.info("tools: %s args=%s -> %s", name, json.dumps(args, ensure_ascii=False)[:120], str(result)[:120]) + return result + except Exception as e: # noqa: BLE001 + log.error("tools: %s 执行失败 %s", name, e, exc_info=True) + return json.dumps({"error": f"{name} 执行失败: {e}"}, ensure_ascii=False) diff --git a/backend/knowledge/kb_index.json b/backend/knowledge/kb_index.json new file mode 100644 index 0000000..481af1c --- /dev/null +++ b/backend/knowledge/kb_index.json @@ -0,0 +1 @@ +{"chunks": ["# 昆明大学生创业园（OPC 园区）", "## 园区简介\n昆明大学生创业园是云南省首家政府主办的大学生创业孵化园区，为大学生创业者提供\"空间+孵化+融资+政策+资源+AI赋能+综合服务\"七位一体的一站式创业服务。", "## 空间服务\n园区提供办公工位、独立办公室、共享会议室、路演大厅、直播基地等创业空间，水电网络全配套，拎包入驻。", "## 孵化服务\n园区为入驻企业提供创业辅导、工商财税、知识产权、法律咨询等孵化服务；配备创业导师团队，提供一对一辅导；定期举办创业大赛、项目路演、融资对接会。", "## 融资服务\n园区对接银行、投资机构、政府引导基金，为入驻企业提供贷款贴息、天使投资、股权融资对接等金融服务。", "## 政策支持\n入驻企业可享受大学生创业补贴、场地租金减免、税收优惠、一次性创业补贴、社保补贴等政府政策；园区协助申报各类科技、人才项目。", "## AI 赋能\n园区建设 OPC 智能运营中心（数字运营平台），通过 PineSound 智能语音助手、数据大屏、YOLO 视觉识别、手势控制等 AI 能力，为企业提供智能咨询、数据洞察与展厅互动服务。", "## 入驻流程\n1. 提交入驻申请（线上/线下）；2. 项目评审；3. 签订入驻协议；4. 办理工商注册；5. 入驻孵化。", "## 园区数据口径\n园区累计孵化企业 200 余家，目前在园企业 150 余家，带动就业 2000 余人，累计营收超 2 亿元，高新技术企业 30 余家，省级以上重点研发项目 18 项，创业大赛奖项 47 项。\n（实时运营数据请调用 get_park_overview 工具获取。）", "## 常见问题\n- 问：如何入驻园区？答：见\"入驻流程\"，可直接联系园区服务台或通过 PineSound 语音助手咨询。\n- 问：园区提供哪些服务？答：见\"孵化服务\"与\"七位一体\"，涵盖空间、孵化、融资、政策、资源、AI 赋能、综合服务。\n- 问：有什么政策支持？答：见\"政策支持\"，包括补贴、租金减免、税收优惠等，具体以最新政策为准。"], "embeddings": [[-0.04334134981036186, 0.04619429633021355, -0.07824110239744186, -0.063702791929245, -0.07675600796937943, -0.0375768318772316, -0.036228522658348083, 0.0433022677898407, 0.016355594620108604, 0.06839257478713989, 0.020791342481970787, 0.035036537796258926, 0.004186602309346199, 0.012203188613057137, 0.056316398084163666, -0.0739421397447586, 0.02821682021021843, 0.013668743893504143, 0.02962375432252884, -0.01059107854962349, -0.008412286639213562, 0.0017586661269888282, 0.010981893166899681, 0.05670721083879471, 0.03153874725103378, -0.003072780556976795, -0.03527102619409561, -0.043458595871925354, -0.06346830725669861, -0.051822029054164886, -0.029838701710104942, -0.004833889193832874, 0.006126020103693008, -0.06976041942834854, -0.07835834473371506, -0.04607705399394035, 0.0007736909901723266, -0.01612110622227192, -0.09809448570013046, 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+园区为入驻企业提供创业辅导、工商财税、知识产权、法律咨询等孵化服务；配备创业导师团队，提供一对一辅导；定期举办创业大赛、项目路演、融资对接会。 + +## 融资服务 +园区对接银行、投资机构、政府引导基金，为入驻企业提供贷款贴息、天使投资、股权融资对接等金融服务。 + +## 政策支持 +入驻企业可享受大学生创业补贴、场地租金减免、税收优惠、一次性创业补贴、社保补贴等政府政策；园区协助申报各类科技、人才项目。 + +## AI 赋能 +园区建设 OPC 智能运营中心（数字运营平台），通过 PineSound 智能语音助手、数据大屏、YOLO 视觉识别、手势控制等 AI 能力，为企业提供智能咨询、数据洞察与展厅互动服务。 + +## 入驻流程 +1. 提交入驻申请（线上/线下）；2. 项目评审；3. 签订入驻协议；4. 办理工商注册；5. 入驻孵化。 + +## 园区数据口径 +园区累计孵化企业 200 余家，目前在园企业 150 余家，带动就业 2000 余人，累计营收超 2 亿元，高新技术企业 30 余家，省级以上重点研发项目 18 项，创业大赛奖项 47 项。 +（实时运营数据请调用 get_park_overview 工具获取。） + +## 常见问题 +- 问：如何入驻园区？答：见"入驻流程"，可直接联系园区服务台或通过 PineSound 语音助手咨询。 +- 问：园区提供哪些服务？答：见"孵化服务"与"七位一体"，涵盖空间、孵化、融资、政策、资源、AI 赋能、综合服务。 +- 问：有什么政策支持？答：见"政策支持"，包括补贴、租金减免、税收优惠等，具体以最新政策为准。 diff --git a/src/pages/VoiceAssistant.jsx b/src/pages/VoiceAssistant.jsx index cafa32b..d6409f4 100644 --- a/src/pages/VoiceAssistant.jsx +++ b/src/pages/VoiceAssistant.jsx @@ -16,10 +16,40 @@ import './voice-original.css'; import './voice-overrides.css'; const VOICE_URL = window.__DPM_VOICE_WS__ || `ws://${window.location.hostname}:8765/v1/realtime`; -const DEFAULT_INSTRUCTIONS = '你是园区智能助手，请用简洁专业的中文回答，不超过三句话。'; +const DEFAULT_INSTRUCTIONS = '你是 PineSound 园区智能语音助手。可用工具：get_park_overview（园区实时数据）、query_companies（企业名录）、control_display（大屏控制）、get_time（时间）。涉及园区数据/企业/大屏控制时务必调用工具获取准确信息。请用简洁专业的中文回答，不超过三句话。'; const DEFAULT_VOICE = 'Cherry'; const DEFAULT_GATE_DB = -50; +// 工具定义（与后端 app/tools.py 的 tool_schemas 一致，经 session.update 传给 LLM） +const TOOL_DEFS = [ + { + type: 'function', name: 'get_park_overview', + description: '获取园区实时运营概览：在园项目数、累计孵化企业、带动就业、营收（今日/累计）、设备在线率、在园人数、能耗等。回答园区数据类问题时使用。', + parameters: { type: 'object', properties: {} }, + }, + { + type: 'function', name: 'query_companies', + description: '查询园区入驻企业名录，支持按企业名关键词过滤。回答"有哪些企业/某企业是否入驻"时使用。', + parameters: { type: 'object', properties: { keyword: { type: 'string', description: '企业名关键词，可为空字符串' } } }, + }, + { + type: 'function', name: 'control_display', + description: '控制大屏显示：switch_page 切换页面、alert 弹通知、media_play/media_pause 控制媒体播放。用户要求控制大屏时使用。', + parameters: { + type: 'object', + properties: { + action: { type: 'string', enum: ['switch_page', 'alert', 'media_play', 'media_pause'] }, + target: { type: 'string', description: '目标：页面路径（如 /、/twin、/ai、/voice）或通知文本' }, + }, + }, + }, + { + type: 'function', name: 'get_time', + description: '获取当前日期时间。用户问"现在几点/今天几号"时使用。', + parameters: { type: 'object', properties: {} }, + }, +]; + const STATE_VIEWS = { idle: '点击开始', connecting: '思考中', @@ -121,6 +151,33 @@ export default function VoiceAssistant() { console.warn('[vision] 自动问候已发送:', GREETING_TEXT); }, []); + // ── 工具调用执行器：LLM 请求工具 → 转发后端 /api/tools/exec → 结果回传 ── + const onToolCall = useCallback(async (e) => { + const { name, arguments: argsStr, callId } = e?.detail ?? {}; + if (!name || !callId) return; + let args = {}; + try { args = JSON.parse(argsStr || '{}'); } catch { /* 忽略非法参数 */ } + console.warn(`[tools] LLM 调用工具: ${name}`, args); + pushMessage('assistant', `🔧 调用工具：${name}`, false); + let output; + try { + const res = await fetch(`${API_BASE}/api/tools/exec`, { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ name, args }), + }); + const data = await res.json(); + output = data?.result ?? JSON.stringify(data); + } catch (err) { + output = JSON.stringify({ error: String(err) }); + } + const c = clientRef.current; + if (c) { + c.sendToolOutput(callId, output); + c.requestResponse(); + } + }, [pushMessage]); + // ── 右下角气泡渲染（复刻原版 ui/chat.js）─────────────────────────────── // 流程：新气泡插入 → rAF 加 `.in`（淡入）→ 4s 后加 `.out`（淡出）→ 400ms 移除。 // 持续更新的气泡（partial 逐字流）续期 4s；栈上限 8 条，最旧优先淡出， @@ -257,11 +314,21 @@ export default function VoiceAssistant() { if (!audioCtxRef.current) audioCtxRef.current = new AudioContext(); if (audioCtxRef.current.state === 'suspended') await audioCtxRef.current.resume(); + // 知识库：拉取园区知识摘要拼进 instructions（静态知识一次注入；失败不影响对话） + let instructions = DEFAULT_INSTRUCTIONS; + try { + const kbRes = await fetch(`${API_BASE}/api/kb/brief`, { cache: 'no-store' }); + const kbData = await kbRes.json(); + if (kbData?.ok && kbData.brief) { + instructions = `${DEFAULT_INSTRUCTIONS}\n\n【园区知识库】\n${kbData.brief}`; + } + } catch { /* 知识库不可用不影响对话 */ } + const client = new S2sWsRealtimeClient({ directUrl: VOICE_URL, voice: DEFAULT_VOICE, - instructions: DEFAULT_INSTRUCTIONS, - tools: [], + instructions, + tools: TOOL_DEFS, noiseGate: { enabled: true, thresholdDb: DEFAULT_GATE_DB }, audioContext: audioCtxRef.current, micStream: stream, @@ -285,6 +352,7 @@ export default function VoiceAssistant() { } }); client.addEventListener('input-level', (e) => paintInputLevel(e.detail?.rms)); + client.addEventListener('toolcall', (e) => void onToolCall(e)); client.addEventListener('response-finished', () => { setState('listening'); // 自动问候的回复播放完毕 → 启动"等待用户回答"倒计时；无回答则自动挂断 @@ -308,7 +376,7 @@ export default function VoiceAssistant() { setErrorMsg(err?.message || String(err)); setState('error'); } - }, [pushMessage, paintInputLevel, sendGreeting]); + }, [pushMessage, paintInputLevel, sendGreeting, onToolCall]); const stop = useCallback(async () => { // 清理自动问候相关状态/倒计时