feat: AI assistant phase 2 - configurable prompt, action operations, FAQ matching, NVIDIA provider

- Admin-configurable AI prompt/quick questions from system_configs DB - GET /api/v1/ai/quick-questions endpoint for fetching quick questions - Local FAQ matching for instant responses (avoid AI calls for common Qs) - AI action extraction: "add customer" intent detected, structured data returned - Frontend action confirmation card with editable fields, calls customer API on confirm - NVIDIA provider (stepfun-ai/step-3.5-flash) for faster chat vs deepseek-v4-flash - Fixed httpx client timeout preventing backend hangs - Added log_usage calls for auth events (register/login/guest/wechat) - Admin tabs (users/stats/logs/config) fully functional with real backend - AiAssistant component added to all tabbar pages
2026-05-20 09:39:22 +08:00
parent 4755cc75ba
commit f8a23855d2
20 changed files with 744 additions and 5 deletions
@@ -0,0 +1,135 @@
+from fastapi import APIRouter, Depends, HTTPException, Request
+from pydantic import BaseModel
+from typing import Optional, List, Dict, Any
+from sqlalchemy.ext.asyncio import AsyncSession
+from sqlalchemy import select
+from app.database import get_db
+from app.ai.router import get_ai_router
+from app.ai.local_faq import match_faq
+from app.api.v1.deps import get_current_user_id
+from app.models.system_config import SystemConfig
+from app.services.admin import AdminService
+import logging
+import time
+import re
+import json
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter()
+
+
+ACTION_INSTRUCTIONS = """
+当用户想要执行操作时（如添加客户、创建产品、生成报价单等），请执行以下步骤：
+1. 从用户消息中提取所有必要的信息
+2. 在回复末尾附上 JSON 格式的动作块，格式如下：
+
+```actions
+[{"type": "create_customer", "label": "添加客户", "fields": {"name": "...", "phone": "...", "email": "...", "company": "...", "country": "...", "notes": "..."}}]
+```
+
+支持的 action type：
+- create_customer：添加客户，fields 支持 name(必填), phone, email, company, country, notes
+- create_product：添加产品（开发中）
+
+如果用户没有提供足够信息，请先询问缺少的字段，不要生成 action。
+如果用户明确表示要执行操作但缺少信息，生成 action 但标注缺失的字段。
+"""
+
+
+class ChatRequest(BaseModel):
+    message: str
+    history: Optional[List[Dict[str, str]]] = None
+
+
+@router.get("/quick-questions")
+async def get_quick_questions(
+    db: AsyncSession = Depends(get_db),
+):
+    result = await db.execute(
+        select(SystemConfig).where(SystemConfig.key == "ai_assistant_quick_questions")
+    )
+    cfg = result.scalar_one_or_none()
+    return cfg.value if cfg and cfg.value else []
+
+
+@router.post("/chat")
+async def chat(
+    data: ChatRequest,
+    request: Request,
+    user_id: str = Depends(get_current_user_id),
+    db: AsyncSession = Depends(get_db),
+):
+    t_start = time.time()
+
+    if not data.message.strip():
+        raise HTTPException(status_code=422, detail="Message is required")
+
+    t0 = time.time()
+    prompt_config = await db.execute(
+        select(SystemConfig).where(SystemConfig.key == "ai_assistant_prompt")
+    )
+    quick_config = await db.execute(
+        select(SystemConfig).where(SystemConfig.key == "ai_assistant_quick_questions")
+    )
+    t1 = time.time()
+
+    prompt_row = prompt_config.scalar_one_or_none()
+    base_prompt = prompt_row.value if prompt_row else None
+    quick_row = quick_config.scalar_one_or_none()
+    quick_questions = quick_row.value if quick_row else None
+    t2 = time.time()
+
+    action_keywords = ["帮我添加", "帮我创建", "帮我新增", "帮我新建", "帮我录入", "帮.+加", "添加客户.*电话", "创建客户.*电话"]
+    needs_action = any(re.search(k, data.message) for k in action_keywords)
+    system_prompt = base_prompt or ""
+    if needs_action:
+        system_prompt += "\n\n" + ACTION_INSTRUCTIONS
+
+    faq_answer = match_faq(data.message)
+    if faq_answer and not needs_action:
+        reply = faq_answer
+        provider = "local-faq"
+        actions = []
+        t4 = time.time()
+        logger.info(
+            f"CHAT [{user_id[:8]}] FAQ match | "
+            f"db={t1-t0:.2f}s orm={t2-t1:.2f}s total={t4-t_start:.2f}s"
+        )
+    else:
+        t3 = time.time()
+        ai = get_ai_router()
+        result = await ai.chat(data.message, data.history or [], system_prompt)
+        t4 = time.time()
+
+        reply = result.get("reply", "")
+        provider = result.get("provider_used", "")
+
+        actions = []
+        action_match = re.search(r'```actions\s*\n(.*?)\n```', reply, re.DOTALL)
+        if action_match:
+            try:
+                actions = json.loads(action_match.group(1))
+                reply = reply[:action_match.start()].strip()
+            except (json.JSONDecodeError, Exception) as e:
+                logger.warning(f"Failed to parse actions: {e}")
+
+        logger.info(
+            f"CHAT [{user_id[:8]}] AI | "
+            f"db={t1-t0:.2f}s orm={t2-t1:.2f}s setup={t3-t2:.2f}s ai={t4-t3:.2f}s total={t4-t_start:.2f}s"
+        )
+
+    client_ip = request.client.host if request.client else None
+    await AdminService(db).log_usage(
+        user_id, "ai.chat",
+        {"message": data.message[:200], "reply_length": len(reply), "provider": provider},
+        ip=client_ip,
+    )
+    logger.info(f"CHAT [{user_id[:8]}] done total={time.time()-t_start:.2f}s")
+
+    return {
+        "reply": reply,
+        "provider": provider,
+        "quick_questions": quick_questions,
+        "actions": actions,
+    }