feat:客服意图识别增加记忆功能
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@@ -1,9 +1,12 @@
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"""Customer-service intent recognition contract."""
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from __future__ import annotations
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import json
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import logging
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import re
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from dataclasses import dataclass
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from enum import StrEnum
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from inspect import isawaitable
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logger = logging.getLogger("rag.intent")
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@@ -26,10 +29,24 @@ INTENT_VALUES = frozenset(item.value for item in Intent)
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_INTENT_PATTERN = re.compile(
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"|".join(re.escape(value) for value in sorted(INTENT_VALUES, key=len, reverse=True))
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)
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_JSON_PATTERN = re.compile(r"\{.*\}", re.S)
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# 改写句允许的最大长度：相对原句的倍数与绝对下限取大者，防止模型把历史大段塞进改写句
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_REWRITE_MAX_RATIO = 4
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_REWRITE_MIN_LIMIT = 200
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INTENT_SYSTEM_PROMPT = (
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"你是华夏科技（一家基金代销金融机构）智能客服的意图分类器。"
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"请根据用户输入，从以下选项中选择最匹配的意图，并仅输出对应的英文标签（不输出任何其他内容）：\n"
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"你会看到最近几轮对话（可能为空）和用户的【当前输入】。\n"
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"任务：\n"
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"1. 只对【当前输入】判定意图；【最近对话】仅用于理解当前输入中省略的主语或指代"
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"（如“它”“那个”“呢”“还有吗”）。\n"
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"2. 若当前输入依赖上文才能理解，请把它改写为一句不依赖上文的完整问题，"
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"只能补全上文已明确出现的对象，不得添加新信息、不得改变原意；"
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"若当前输入本身已完整，query 原样返回。\n"
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"3. 当前输入若明显切换到新话题，以当前输入为准，不要延续上一轮的意图。\n"
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"4. 致谢、告别、寒暄即使出现在知识问答之后也归为 chitchat。\n"
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"意图选项：\n"
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"- guide_purchase: 用户询问如何购买基金、开户、注册等引导类问题\n"
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"- want_advisor: 用户希望获得个性化基金推荐或投资顾问服务\n"
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"- knowledge_qa: 用户询问基金相关的知识性问题，如净值、费率、风险、申赎规则等\n"
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@@ -41,10 +58,26 @@ INTENT_SYSTEM_PROMPT = (
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"如写代码、讲笑话、写作文、问天气、聊政治、情感咨询、做数学题等\n"
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"- no_match: 无法归入以上任何一类\n"
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"注意：寒暄性质的一两句话归为 chitchat；一旦用户提出金融之外的实质性请求，归为 off_topic。\n"
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"仅输出一个小写英文标签，不要输出解释、标点或换行。"
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"只输出一行 JSON，格式：{\"intent\": \"<小写英文标签>\", \"query\": \"<完整问题>\"}，"
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"不要输出解释、Markdown 或其他内容。"
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)
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@dataclass(frozen=True)
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class IntentResult:
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intent: Intent
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# 结合历史补全后的独立问题；无需补全或解析失败时等于原句
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query: str
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used_history: bool = False
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async def _config_value(config_getter, key: str, default):
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value = config_getter(key, str(default))
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if isawaitable(value):
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value = await value
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return type(default)(value)
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def parse_intent(raw: str | None) -> Intent:
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"""从模型原始输出中提取第一个合法标签，提取不到则返回 NO_MATCH。"""
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if not raw:
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@@ -53,16 +86,77 @@ def parse_intent(raw: str | None) -> Intent:
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return Intent(match.group(0)) if match else Intent.NO_MATCH
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async def intent_recognize(query: str, *, llm_client) -> Intent:
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if not query or not query.strip():
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return Intent.NO_MATCH
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messages = [
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def parse_intent_result(raw: str | None, *, fallback_query: str, used_history: bool = False) -> IntentResult:
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"""优先按 JSON 解析意图与改写句；JSON 不可用时退回正则抽标签、原句作为 query。"""
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match = _JSON_PATTERN.search(raw) if raw else None
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data = None
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if match:
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try:
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data = json.loads(match.group(0))
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except ValueError:
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data = None
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if not isinstance(data, dict):
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return IntentResult(parse_intent(raw), fallback_query, used_history)
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intent = parse_intent(str(data.get("intent") or ""))
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rewritten = str(data.get("query") or "").strip()
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limit = max(len(fallback_query) * _REWRITE_MAX_RATIO, _REWRITE_MIN_LIMIT)
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query = rewritten if rewritten and len(rewritten) <= limit else fallback_query
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return IntentResult(intent, query, used_history)
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def render_history(history, *, max_turns: int, max_chars: int) -> str:
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"""把最近 max_turns 轮 user/assistant 消息折叠成一段文本，每条截断到 max_chars。"""
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if max_turns <= 0 or not history:
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return ""
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recent = [
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message for message in history
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if isinstance(message, dict)
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and message.get("role") in ("user", "assistant")
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and message.get("content")
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][-max_turns * 2:]
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lines = []
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for message in recent:
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role = "用户" if message["role"] == "user" else "客服"
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content = str(message["content"]).replace("\n", " ").strip()
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if len(content) > max_chars:
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content = content[:max_chars] + "…"
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lines.append(f"{role}：{content}")
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return "\n".join(lines)
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def build_intent_messages(query: str, rendered_history: str) -> list[dict]:
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if rendered_history:
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user_content = f"【最近对话】\n{rendered_history}\n\n【当前输入】\n{query}"
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else:
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user_content = f"【当前输入】\n{query}"
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return [
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{"role": "system", "content": INTENT_SYSTEM_PROMPT},
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{"role": "user", "content": query},
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{"role": "user", "content": user_content},
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]
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async def intent_recognize(
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query: str,
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*,
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llm_client,
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history: list[dict] | None = None,
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config_getter=None,
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) -> IntentResult:
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"""结合最近几轮对话识别当前输入的意图，并给出补全指代后的独立问题。
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history 为空或 agent.customer.intent.history_turns 配置为 0 时退化为仅看当前句。
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"""
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if not query or not query.strip():
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return IntentResult(Intent.NO_MATCH, query or "")
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max_turns, max_chars = 3, 200
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if config_getter is not None:
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max_turns = await _config_value(config_getter, "agent.customer.intent.history_turns", max_turns)
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max_chars = await _config_value(config_getter, "agent.customer.intent.history_max_chars", max_chars)
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rendered = render_history(history, max_turns=max_turns, max_chars=max_chars)
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messages = build_intent_messages(query, rendered)
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try:
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raw = await llm_client.chat(messages)
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except Exception:
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logger.exception("intent recognition failed")
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return Intent.NO_MATCH
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return parse_intent(raw)
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return IntentResult(Intent.NO_MATCH, query, bool(rendered))
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return parse_intent_result(raw, fallback_query=query, used_history=bool(rendered))
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@@ -207,8 +207,13 @@ def build_client_runtime(
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config_getter=config_getter,
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)
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async def recognize(query):
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return await intent_recognize(query, llm_client=llm_client)
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async def recognize(query, history=None):
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return await intent_recognize(
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query,
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llm_client=llm_client,
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history=history,
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config_getter=config_getter,
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)
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async def generate(messages):
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memory_context = _active_memory_context.get()
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@@ -2,10 +2,14 @@
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from __future__ import annotations
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import json
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import logging
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import re
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from inspect import isawaitable
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from rag.intent import Intent
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from rag.intent import Intent, IntentResult
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logger = logging.getLogger(__name__)
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class QueryTooLongError(ValueError):
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@@ -44,6 +48,12 @@ class AnonymousCustomerAgent:
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async def handle(self, session_id: str, query: str, *, trace_id: str) -> dict:
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if len(query) > 2000:
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raise QueryTooLongError("query长度不能超过2000字符")
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# 先取历史再写入当前问题，保证意图识别拿到的历史不含本轮输入；取不到历史不阻断请求
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try:
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history = await self.context.get(session_id)
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except Exception:
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logger.exception("load conversation history failed: session_id=%s", session_id)
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history = []
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await self.context.append(session_id, "user", query)
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if self._contains_sensitive_input(query):
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await _maybe_await(self.audit_writer(
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@@ -52,7 +62,11 @@ class AnonymousCustomerAgent:
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session_id=session_id,
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))
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intent = await _maybe_await(self.intent_recognize(query))
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recognized = await _maybe_await(self.intent_recognize(query, history))
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if isinstance(recognized, IntentResult):
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intent, search_query = recognized.intent, recognized.query
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else:
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intent, search_query = recognized, query
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sources = []
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if intent == Intent.GUIDE_PURCHASE:
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answer = await _config(
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@@ -77,7 +91,8 @@ class AnonymousCustomerAgent:
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answer = await self._chitchat(session_id)
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elif intent in (Intent.KNOWLEDGE_QA, Intent.COMPANY_INFO):
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try:
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sources = await _maybe_await(self.rag_retrieve(query, None))
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# 用补全指代后的问题检索，省略主语的追问才能命中
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sources = await _maybe_await(self.rag_retrieve(search_query, None))
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except Exception:
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sources = []
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if not sources:
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@@ -118,6 +133,7 @@ class AnonymousCustomerAgent:
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"answer": answer,
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"sources": sources,
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"intent": intent.value,
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"rewritten_query": search_query,
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"trace_id": trace_id,
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}
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@@ -36,8 +36,13 @@ def build_anonymous_runtime(
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config_getter=config_getter,
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)
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async def recognize(query):
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return await intent_recognize(query, llm_client=llm_client)
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async def recognize(query, history=None):
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return await intent_recognize(
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query,
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llm_client=llm_client,
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history=history,
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config_getter=config_getter,
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)
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async def generate(messages):
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return await generate_answer(
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