feat: adaptive debounce and intent-driven quote trigger tuning
This commit is contained in:
@@ -1487,7 +1487,11 @@ class CustomerServiceAgent:
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state.image_count = len(state.pending_image_urls)
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state.image_count = len(state.pending_image_urls)
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self._sync_pending_quote_state(message.from_id, state)
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self._sync_pending_quote_state(message.from_id, state)
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if self._is_batch_finish_signal(customer_text):
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if self._is_batch_finish_intent(
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text=customer_text,
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state=state,
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has_incoming_urls=bool(incoming_urls),
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):
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quote_res = await self._quote_pending_images(state, message)
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quote_res = await self._quote_pending_images(state, message)
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reply_text = quote_res.get("reply", "")
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reply_text = quote_res.get("reply", "")
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need_transfer = bool(quote_res.get("need_transfer"))
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need_transfer = bool(quote_res.get("need_transfer"))
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@@ -1509,7 +1513,11 @@ class CustomerServiceAgent:
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if text_without_urls:
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if text_without_urls:
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self._append_requirement(state, text_without_urls)
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self._append_requirement(state, text_without_urls)
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self._sync_pending_quote_state(message.from_id, state)
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self._sync_pending_quote_state(message.from_id, state)
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if self._is_batch_finish_signal(customer_text):
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if self._is_batch_finish_intent(
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text=customer_text,
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state=state,
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has_incoming_urls=False,
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):
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quote_res = await self._quote_pending_images(state, message)
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quote_res = await self._quote_pending_images(state, message)
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reply_text = quote_res.get("reply", "")
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reply_text = quote_res.get("reply", "")
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need_transfer = bool(quote_res.get("need_transfer"))
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need_transfer = bool(quote_res.get("need_transfer"))
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@@ -2057,23 +2065,86 @@ class CustomerServiceAgent:
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]
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]
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return any(k in text for k in finish_keywords)
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return any(k in text for k in finish_keywords)
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def _is_batch_finish_intent(
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self,
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text: str,
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state: ConversationState,
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has_incoming_urls: bool,
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) -> bool:
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"""
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语义结束识别:
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- 显式口令:发完了/统一报价
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- 隐式意图:询价/砍价
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- 单图需求明确:如“这个门头上面的字做一下”可直接进入报价
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"""
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if not text:
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return False
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if self._is_batch_finish_signal(text):
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return True
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if has_incoming_urls:
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return False
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if not state.pending_image_urls:
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return False
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# 意图识别:询价/砍价通常意味着“可以报价了”
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try:
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from utils.intent_analyzer import detect_intent_embedding, detect_intent_keywords
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intent = detect_intent_embedding(text) or detect_intent_keywords(text)
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except Exception:
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intent = ""
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if intent in ("询价", "砍价"):
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return True
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msg = (text or "").strip()
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if not msg:
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return False
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# 单图场景:客户给出明确加工指令,可直接报价
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single_image_action_kw = (
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"做一下", "改一下", "处理一下", "就这张", "按这个做", "照这个做",
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"这个门头", "上面的字", "这个字", "这个图做", "能做吗",
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)
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multi_image_finish_kw = (
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"就这些", "就这几张", "按这几张", "这几张一起做", "一起做一下",
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"先按这些", "先按这几张", "直接报价", "现在报价", "看下报价",
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"先报个总价", "总价多少", "一起多少钱", "先做这几张",
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)
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hold_kw = ("还有", "再发", "先等", "稍后", "等会", "回头")
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if len(state.pending_image_urls) == 1:
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if any(k in msg for k in single_image_action_kw) and not any(k in msg for k in hold_kw):
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return True
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elif len(state.pending_image_urls) >= 2:
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if any(k in msg for k in multi_image_finish_kw) and not any(k in msg for k in hold_kw):
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return True
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return False
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def _build_collect_ack(self, count: int) -> str:
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def _build_collect_ack(self, count: int) -> str:
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if count <= 1:
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if count <= 1:
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return "收到这张图了,你还有图就继续发;发完我再一起给你报价。"
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one_templates = [
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"这张收到啦,还有图就继续发,我一起给你看。",
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"图我看到了,后面还有就接着发,最后我一口价给你。",
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"收到这张了,你有其他图也发来,我统一帮你算。",
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]
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return random.choice(one_templates)
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templates = [
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templates = [
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"收到,这边先记下了(已收{n}张)。你继续发,等你发完我再一起给你打包报价。",
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"这几张我都收到了(现在{n}张)。还有的话继续发,我一起给你报。",
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"好的,当前这批先收到了(第{n}张)。还有图就继续发,发齐我一次性给你总价。",
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"好嘞,先看到{n}张了。你可以继续发,或者直接说“就这些”我现在就报价。",
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"没问题,已记录到第{n}张。你把需求和图片都发完,我统一给你报更合适的价格。",
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"收到哈(共{n}张)。你还要补图就继续发,不补的话我现在也可以直接给价。",
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]
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]
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return random.choice(templates).format(n=count)
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return random.choice(templates).format(n=count)
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def _build_collect_remind(self, count: int) -> str:
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def _build_collect_remind(self, count: int) -> str:
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if count <= 1:
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if count <= 1:
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return "需求我记下了。你如果还有图继续发,发完回我“发完了”,我给你报价。"
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one_templates = [
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"这个要求我记住了。你还有图就继续发,不补图我就按这张给你报价。",
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"明白,这个需求我加上了。你继续发图也行,想直接报价也可以。",
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"收到,我按你这个要求做。你要是就这张,我现在就能给你报价。",
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]
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return random.choice(one_templates)
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templates = [
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templates = [
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"需求我记下了(当前共{n}张图)。你继续发齐,发完回我“发完了”,我一次性给你总价。",
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"需求我记下了(当前{n}张)。你继续补图,或者直接说“就这些”我现在报价。",
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"好的,这条需求也加上了(现在{n}张)。等你说发完,我立刻统一报价。",
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"好,这个要求也加上了(现在{n}张)。不再补图的话我立刻给你打包价。",
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"收到,这个要求我也记住了(共{n}张)。你发完我就给你打包价。",
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"收到(共{n}张)。你还发就继续,不发的话我现在就给总价。",
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]
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]
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return random.choice(templates).format(n=count)
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return random.choice(templates).format(n=count)
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@@ -2149,19 +2220,34 @@ class CustomerServiceAgent:
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# 单图时不要使用“分图/这批/A-B方案”措辞,避免客户误解为多图。
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# 单图时不要使用“分图/这批/A-B方案”措辞,避免客户误解为多图。
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if len(results) == 1:
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if len(results) == 1:
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line = detail_lines[0].replace("图1:", "这张:")
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line = detail_lines[0].replace("图1:", "这张:")
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lines = [f"给你报下这张:{line.split(':', 1)[1]}"]
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heads = [
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"这张我看过了,先给你报下:",
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"这张可以做,价格给你报下:",
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"看了这张图,报价如下:",
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]
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lines = [f"{random.choice(heads)}{line.split(':', 1)[1]}"]
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if req_hit:
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if req_hit:
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lines.append(f"按你的需求另加{extra}元({req_hit})。")
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lines.append(f"按你的需求另加{extra}元({req_hit})。")
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lines.append(f"这张做下来共{single_total}元,可以的话我马上安排。")
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tails = [
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f"这张做下来共{single_total}元,定了我马上开工。",
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f"合下来是{single_total}元,你点头我这边立刻安排。",
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f"总价{single_total}元,可以的话我现在就给你做。",
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]
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lines.append(random.choice(tails))
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return "\n".join(lines)
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return "\n".join(lines)
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lines = ["先给你分图报下:"]
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heads = [
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"我先按这几张给你报一下:",
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"这几张我都看过了,价格给你列一下:",
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"我把每张价格先给你说清楚:",
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]
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lines = [random.choice(heads)]
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lines.extend(detail_lines)
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lines.extend(detail_lines)
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if req_hit:
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if req_hit:
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lines.append(f"需求加价:+{extra}元({req_hit})")
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lines.append(f"需求加价:+{extra}元({req_hit})")
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option_line = f"可选:A按单张做共{single_total}元;B打包一起做{bundle_price}元(更划算)。"
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option_line = f"可选:按单张做(共{single_total}元),或打包做({bundle_price}元,会更省一点)。"
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lines.append(option_line)
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lines.append(option_line)
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lines.append("你定一个方案,我这边马上安排。")
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lines.append("你定一个,我这边马上开工。")
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return "\n".join(lines)
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return "\n".join(lines)
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def _prepare_batch_intake(self, state: ConversationState) -> Dict[str, Any]:
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def _prepare_batch_intake(self, state: ConversationState) -> Dict[str, Any]:
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@@ -4,6 +4,7 @@ import json
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import re
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import re
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import logging
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import logging
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import random
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import random
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import secrets
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import time
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import time
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import hashlib
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import hashlib
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from collections import deque
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from collections import deque
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@@ -88,6 +89,7 @@ class QingjianAPIClient:
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# 消息防抖:同一客户连续发消息时,等待 N 秒后合并处理
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# 消息防抖:同一客户连续发消息时,等待 N 秒后合并处理
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self._DEBOUNCE_SECONDS = MESSAGE_DEBOUNCE_SECONDS if isinstance(MESSAGE_DEBOUNCE_SECONDS, int) else 8
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self._DEBOUNCE_SECONDS = MESSAGE_DEBOUNCE_SECONDS if isinstance(MESSAGE_DEBOUNCE_SECONDS, int) else 8
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self._adaptive_debounce_enabled = os.getenv("ADAPTIVE_DEBOUNCE_ENABLED", "true").lower() in ("1", "true", "yes")
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self._debounce_tasks: dict = {} # customer_key -> asyncio.Task
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self._debounce_tasks: dict = {} # customer_key -> asyncio.Task
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self._pending_msgs: dict = {} # customer_key -> list[data]
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self._pending_msgs: dict = {} # customer_key -> list[data]
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self._image_enabled = IMAGE_MODULE_ENABLED
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self._image_enabled = IMAGE_MODULE_ENABLED
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@@ -436,9 +438,11 @@ class QingjianAPIClient:
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if old_task and not old_task.done():
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if old_task and not old_task.done():
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old_task.cancel()
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old_task.cancel()
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debounce_seconds = self._pick_debounce_seconds(data, msg_body)
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# 创建新的延迟处理任务
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# 创建新的延迟处理任务
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async def _delayed(capture_key, capture_data):
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async def _delayed(capture_key, capture_data, wait_s: float):
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await asyncio.sleep(self._DEBOUNCE_SECONDS)
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await asyncio.sleep(wait_s)
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msgs = self._pending_msgs.pop(capture_key, [])
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msgs = self._pending_msgs.pop(capture_key, [])
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if not msgs:
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if not msgs:
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return
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return
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@@ -451,9 +455,88 @@ class QingjianAPIClient:
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merged_data['msg'] = merged_msg
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merged_data['msg'] = merged_msg
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await self._agent_reply_serialized(merged_data)
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await self._agent_reply_serialized(merged_data)
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task = asyncio.create_task(_delayed(key, data))
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task = asyncio.create_task(_delayed(key, data, debounce_seconds))
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self._debounce_tasks[key] = task
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self._debounce_tasks[key] = task
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@staticmethod
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def _rand_between(low: float, high: float) -> float:
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if high <= low:
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return float(low)
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# 使用 secrets 增强随机性,避免固定周期导致机械感
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span = high - low
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return round(low + span * (secrets.randbelow(1000) / 1000.0), 2)
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def _guess_intent_for_debounce(self, msg: str) -> str:
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text = (msg or "").strip()
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if not text:
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return "unknown"
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if self._msg_has_image_url(text):
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return "image"
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try:
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from utils.intent_analyzer import detect_intent_keywords
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intent = detect_intent_keywords(text)
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except Exception:
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intent = ""
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if intent:
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return intent
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lower = text.lower()
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if any(k in lower for k in ["报价", "多少钱", "价格", "贵", "优惠"]):
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return "询价"
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if any(k in lower for k in ["做一下", "改一下", "需求", "门头", "上面的字", "处理"]):
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return "修改"
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if any(k in lower for k in ["在吗", "你好", "有人"]):
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return "打招呼"
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return "unknown"
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@staticmethod
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def _looks_like_requirement_text(msg: str) -> bool:
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text = (msg or "").strip().lower()
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if not text:
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return False
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req_kw = (
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"做一下", "改一下", "处理一下", "这个字", "上面的字", "门头", "去背景", "抠图",
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"换色", "调色", "清晰", "高清", "尺寸", "比例", "横版", "竖版", "排版", "改字",
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"按这个做", "照这个做", "就这张", "看看做", "弄一下",
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)
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return any(k in text for k in req_kw)
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def _pick_debounce_seconds(self, data: dict, msg: str) -> float:
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"""意图驱动防抖:不同意图不同等待区间,并引入轻微随机。"""
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base = max(1.0, float(self._DEBOUNCE_SECONDS))
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if not self._adaptive_debounce_enabled:
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return base
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intent = self._guess_intent_for_debounce(msg)
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is_req = self._looks_like_requirement_text(msg)
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has_img = self._msg_has_image_url(msg)
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# 区间策略:越明确、越短消息,等待越短;需求描述类稍长
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if intent == "打招呼":
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low, high = 1.0, min(3.0, base)
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elif intent in ("询价", "砍价"):
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low, high = 2.0, min(5.0, base)
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elif intent in ("修改", "批量"):
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low, high = max(3.0, base * 0.65), min(18.0, base + 2.0)
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elif intent == "转接":
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low, high = 1.0, 2.5
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else:
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low, high = max(2.0, base * 0.5), base
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# 发图后的需求描述,优先“多等一点”收集完整需求,减少半句回复
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if is_req and not has_img:
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low = max(low, min(10.0, base * 0.8))
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high = max(high, min(20.0, base + 4.0))
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# 短句更快,长句稍慢,避免把连续半句拆开
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text_len = len((msg or "").strip())
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if text_len <= 4:
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high = min(high, max(low + 0.2, 2.5))
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||||||
|
elif text_len >= 18:
|
||||||
|
low = min(high, low + 0.6)
|
||||||
|
|
||||||
|
wait_s = self._rand_between(low, high)
|
||||||
|
logger.info(f"防抖等待 {wait_s}s | intent={intent} | len={text_len}")
|
||||||
|
return wait_s
|
||||||
|
|
||||||
def _msg_has_image_url(self, msg: str) -> bool:
|
def _msg_has_image_url(self, msg: str) -> bool:
|
||||||
"""判断文本消息里是否包含图片URL(客户粘贴了图片链接,可能带前缀文字如 有吗#*#https://...)"""
|
"""判断文本消息里是否包含图片URL(客户粘贴了图片链接,可能带前缀文字如 有吗#*#https://...)"""
|
||||||
if not msg:
|
if not msg:
|
||||||
|
|||||||
@@ -61,6 +61,58 @@ class RegressionPipelineTest(unittest.IsolatedAsyncioTestCase):
|
|||||||
self.assertIn("15", resp.reply)
|
self.assertIn("15", resp.reply)
|
||||||
agent._quote_pending_images.assert_awaited()
|
agent._quote_pending_images.assert_awaited()
|
||||||
|
|
||||||
|
async def test_single_image_requirement_intent_triggers_quote(self):
|
||||||
|
agent = CustomerServiceAgent()
|
||||||
|
st = agent._get_conversation_state(self.customer_id)
|
||||||
|
st.pending_image_urls = ["https://img.alicdn.com/a.jpg"]
|
||||||
|
st.pending_requirements = []
|
||||||
|
agent._sync_pending_quote_state(self.customer_id, st)
|
||||||
|
agent._quote_pending_images = AsyncMock(return_value={"reply": "这张20元,定了我马上做", "need_transfer": False})
|
||||||
|
|
||||||
|
msg = CustomerMessage(
|
||||||
|
msg_id="m3",
|
||||||
|
acc_id="test_shop",
|
||||||
|
msg="这个门头上面的字做一下",
|
||||||
|
from_id=self.customer_id,
|
||||||
|
from_name="t",
|
||||||
|
cy_id=self.customer_id,
|
||||||
|
acc_type="AliWorkbench",
|
||||||
|
msg_type=0,
|
||||||
|
cy_name="t",
|
||||||
|
goods_name="专业找图",
|
||||||
|
goods_order="",
|
||||||
|
)
|
||||||
|
resp = await agent.process_message(msg)
|
||||||
|
self.assertTrue(resp.should_reply)
|
||||||
|
self.assertIn("20", resp.reply)
|
||||||
|
agent._quote_pending_images.assert_awaited()
|
||||||
|
|
||||||
|
async def test_multi_image_finish_intent_triggers_quote(self):
|
||||||
|
agent = CustomerServiceAgent()
|
||||||
|
st = agent._get_conversation_state(self.customer_id)
|
||||||
|
st.pending_image_urls = ["https://img.alicdn.com/a.jpg", "https://img.alicdn.com/b.jpg"]
|
||||||
|
st.pending_requirements = ["改字"]
|
||||||
|
agent._sync_pending_quote_state(self.customer_id, st)
|
||||||
|
agent._quote_pending_images = AsyncMock(return_value={"reply": "两张打包45,定了我就开做", "need_transfer": False})
|
||||||
|
|
||||||
|
msg = CustomerMessage(
|
||||||
|
msg_id="m4",
|
||||||
|
acc_id="test_shop",
|
||||||
|
msg="就这几张,先按这些报个价",
|
||||||
|
from_id=self.customer_id,
|
||||||
|
from_name="t",
|
||||||
|
cy_id=self.customer_id,
|
||||||
|
acc_type="AliWorkbench",
|
||||||
|
msg_type=0,
|
||||||
|
cy_name="t",
|
||||||
|
goods_name="专业找图",
|
||||||
|
goods_order="",
|
||||||
|
)
|
||||||
|
resp = await agent.process_message(msg)
|
||||||
|
self.assertTrue(resp.should_reply)
|
||||||
|
self.assertIn("45", resp.reply)
|
||||||
|
agent._quote_pending_images.assert_awaited()
|
||||||
|
|
||||||
async def test_pending_state_restore(self):
|
async def test_pending_state_restore(self):
|
||||||
db.update_pending_quote_state(self.customer_id, ["u1", "u2"], ["r1"])
|
db.update_pending_quote_state(self.customer_id, ["u1", "u2"], ["r1"])
|
||||||
agent = CustomerServiceAgent()
|
agent = CustomerServiceAgent()
|
||||||
|
|||||||
Reference in New Issue
Block a user