hankin
423baff73b
- Docker bridge 网络隔离（8000 端口封死） - Gunicorn 4 Worker 多进程 - Alembic 数据库迁移基线 - 日志轮转 20m×3 - JWT 密钥 + DB 密码 + CORS 收紧 - 3-2-1 备份链路（NAS + R740-B 冷备） - 连接池 pool_pre_ping + pool_recycle=3600
109 lines
4.8 KiB
Python
109 lines
4.8 KiB
Python
"""
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意图分类服务 — 基于 4060 节点 Qwen3.5-4B
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将用户输入快速分类为不同的意图类型，用于路由到对应的处理逻辑。
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"""
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from __future__ import annotations
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import json
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import re
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import httpx
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from app.core.config import settings
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# 意图 → Dify App 路由映射（可扩展）
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INTENT_ROUTES = {
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"crm": "dify_agent", # 客户、订单、产品、发货等 CRM 操作
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"finance": "dify_agent", # 财务、报销、票据操作
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"knowledge": "dify_agent", # 知识库问答（未来可以指向独立的 RAG App）
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"general": "dify_agent", # 通用闲聊
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"report": "dify_workflow_report", # 周报/月报生成
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}
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SYSTEM_PROMPT = """你是一个意图分类器。根据用户输入，判断它属于以下哪个意图类别。只返回 JSON 格式 {"intent": "xxx", "confidence": 0.xx}。
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意图类别:
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- crm: 客户管理(查询/新建客户)、订单管理(查询/下单)、产品/库存、发货物流
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- finance: 报销、票据、发票、财务审批
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- report: 生成周报、月报、工作汇报
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- knowledge: 产品知识、技术问答、公司规章制度
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- general: 日常闲聊、问候、与业务无关的问题
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只输出 JSON，不要解释。"""
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async def classify_intent(message: str) -> dict:
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"""
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调用 4060 上的 Qwen3.5-4B 做快速意图分类。
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返回 {"intent": "crm", "confidence": 0.95, "route": "dify_agent"}
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如果分类失败，默认路由到 dify_agent。
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"""
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fallback = {"intent": "general", "confidence": 0.0, "route": "dify_agent"}
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if not settings.OLLAMA_4060_BASE_URL:
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return fallback
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url = f"{settings.OLLAMA_4060_BASE_URL}/api/chat"
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payload = {
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"model": settings.OLLAMA_4060_MODEL,
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"messages": [
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": message},
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],
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"stream": False,
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"options": {
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"temperature": 0.1,
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"num_predict": 500, # Qwen3.5 的 CoT thinking 会消耗较多 token
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},
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}
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try:
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async with httpx.AsyncClient(timeout=10.0) as client:
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resp = await client.post(url, json=payload)
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if resp.status_code != 200:
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print(f"[IntentGateway] 4060 返回 {resp.status_code}: {resp.text[:200]}")
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return fallback
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data = resp.json()
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# Qwen3.5 的 CoT 推理放在 message.thinking 字段，最终结果在 message.content
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content = data.get("message", {}).get("content", "")
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thinking = data.get("message", {}).get("thinking", "")
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# 优先从 content 提取 JSON，回退到 thinking
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for text_source in [content, thinking]:
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if not text_source:
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continue
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# 去掉 <think>...</think> 块
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cleaned = re.sub(r'<think>.*?</think>', '', text_source, flags=re.DOTALL).strip()
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json_match = re.search(r'\{[^}]+\}', cleaned)
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if json_match:
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try:
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result = json.loads(json_match.group())
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intent = result.get("intent", "general")
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confidence = float(result.get("confidence", 0.0))
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route = INTENT_ROUTES.get(intent, "dify_agent")
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print(f"[IntentGateway] intent={intent}, confidence={confidence:.2f}, route={route}")
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return {"intent": intent, "confidence": confidence, "route": route}
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except json.JSONDecodeError:
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continue
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# 从 thinking 内容中启发式推断意图（当 JSON 未生成完成时）
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combined = (thinking + " " + content).lower()
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if any(kw in combined for kw in ["crm", "customer", "客户", "订单", "order"]):
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print(f"[IntentGateway] 启发式推断: crm")
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return {"intent": "crm", "confidence": 0.7, "route": "dify_agent"}
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if any(kw in combined for kw in ["finance", "报销", "发票", "票据", "财务"]):
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print(f"[IntentGateway] 启发式推断: finance")
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return {"intent": "finance", "confidence": 0.7, "route": "dify_agent"}
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if any(kw in combined for kw in ["report", "周报", "月报", "汇报"]):
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print(f"[IntentGateway] 启发式推断: report")
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return {"intent": "report", "confidence": 0.7, "route": "dify_workflow_report"}
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print(f"[IntentGateway] JSON 解析失败, 内容长度: content={len(content)}, thinking={len(thinking)}")
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return fallback
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except httpx.TimeoutException:
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print("[IntentGateway] 4060 超时，降级到默认路由")
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return fallback
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except Exception as e:
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print(f"[IntentGateway] 错误: {e}")
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return fallback
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