refactor: extract prompt building and image workflow routing from agent
This commit is contained in:
52
core/image_workflow_router.py
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52
core/image_workflow_router.py
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@@ -0,0 +1,52 @@
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from __future__ import annotations
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from typing import Any
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async def handle_image_workflow(*, workflow_router: Any, message: str, data: dict, image_urls: list) -> bool:
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"""处理图片工作流（根据客户说的话判断执行哪种工作流）。"""
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if not image_urls:
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return False
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workflow_type, confidence = workflow_router.detect_workflow(message)
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customer_id = data.get("from_id")
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acc_id = data.get("acc_id", "")
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acc_type = data.get("acc_type", "AliWorkbench")
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image_url = image_urls[0]
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print(f"[Agent] 检测到工作流类型：{workflow_type} (置信度：{confidence})")
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if workflow_type == "find_image":
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print(f"[Agent] 执行查找图片工作流 | 客户：{customer_id}")
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from core.workflow import workflow
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return await workflow.find_image_workflow(
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customer_id=customer_id,
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image_url=image_url,
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acc_id=acc_id,
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acc_type=acc_type,
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)
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if workflow_type == "process_image":
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print(f"[Agent] 执行处理图片工作流 | 客户：{customer_id}")
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from core.workflow import workflow
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return await workflow.process_image_workflow(
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customer_id=customer_id,
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image_url=image_url,
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acc_id=acc_id,
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acc_type=acc_type,
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)
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if workflow_type == "transfer_human":
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print(f"[Agent] 执行转人工派单工作流 | 客户：{customer_id}")
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from core.workflow import workflow
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return await workflow.transfer_to_designer_workflow(
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customer_id=customer_id,
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image_url=image_url,
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acc_id=acc_id,
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acc_type=acc_type,
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reason="客户主动要求转人工",
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)
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return False
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187
core/prompt_builder.py
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187
core/prompt_builder.py
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@@ -0,0 +1,187 @@
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from __future__ import annotations
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import re
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from typing import Any, Callable
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def split_customer_text(msg: str) -> tuple[str, str]:
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"""
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把混合消息拆分为（客户真实文字, 系统订单块）。
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平台有时把客户文字和系统订单通知拼在同一条消息里。
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"""
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order_marker = re.search(r"\[系统订单信息\]|\[系统通知\]", msg or "")
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if order_marker:
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customer_text = (msg or "")[: order_marker.start()].strip()
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order_block = (msg or "")[order_marker.start() :].strip()
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else:
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customer_text = (msg or "").strip()
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order_block = ""
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return customer_text, order_block
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def build_prompt(
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*,
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message: Any,
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state: Any,
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extract_image_url: Callable[[str], str],
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shop_type_resolver: Callable[[str, str], str],
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parse_order_info: Callable[[str], dict[str, str]],
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build_order_instruction: Callable[[str, str], str],
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) -> str:
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"""构建提示词。"""
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msg_content = message.msg
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stage_info = f"【当前阶段】{state.stage}"
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customer_text, order_block = split_customer_text(msg_content)
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has_order = bool(order_block)
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if has_order:
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order = parse_order_info(order_block)
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if order.get("order_id"):
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state.last_order_id = order["order_id"]
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stage_info += f"\n【订单号】{order['order_id']}"
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if order.get("order_status"):
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state.order_status = order["order_status"]
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stage_info += f"\n【订单状态】{order['order_status']}"
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if order.get("pay_status"):
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stage_info += f"\n【支付状态】{order['pay_status']}"
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if order.get("amount"):
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stage_info += f"\n【订单金额】{order['amount']}元"
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if order.get("quantity"):
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stage_info += f"\n【数量】{order['quantity']}件"
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if order.get("order_time"):
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stage_info += f"\n【下单时间】{order['order_time']}"
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if order.get("buyer_note"):
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stage_info += f"\n【买家备注】{order['buyer_note']}"
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if state.discount_count > 0:
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stage_info += f"\n【客户压价次数】{state.discount_count}"
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shop_type = shop_type_resolver(message.acc_id or "", message.goods_name or "")
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shop_hint = ""
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try:
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from config.config import CONFIG_DIR
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import json
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cfg_path = CONFIG_DIR / "shop_prompts.json"
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if cfg_path.exists():
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with open(cfg_path, "r", encoding="utf-8") as f:
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cfg = json.load(f)
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hints = cfg.get("type_hints", {})
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shop_hint = hints.get(shop_type, "")
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if not shop_hint and message.acc_id:
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sh = cfg.get("shops", {}).get(message.acc_id, {})
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shop_hint = sh.get("hint", "")
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except Exception:
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pass
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prompt = f"""收到新消息：
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{stage_info}
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发送者: {message.from_name} ({message.from_id})
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"""
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if message.goods_name:
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prompt += f"商品名称: {message.goods_name}\n"
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if shop_hint:
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prompt += f"\n{shop_hint}\n"
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order_paid = False
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order_unpaid = False
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if has_order:
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order = parse_order_info(order_block)
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paid_kws = ["等待发货", "已付款", "付款成功", "买家已付款"]
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unpaid_kws = ["等待买家付款", "待付款", "未付款"]
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ps = order.get("pay_status", "")
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os_ = order.get("order_status", "")
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if any(kw in ps or kw in os_ for kw in paid_kws):
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order_paid = True
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elif any(kw in ps or kw in os_ for kw in unpaid_kws):
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order_unpaid = True
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progress_keywords = [
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"安排了吗",
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"安排好了吗",
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"好了吗",
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"做了吗",
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"做好了吗",
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"弄好了吗",
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"好了没",
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"做了没",
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"什么时候好",
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"多久好",
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"进度",
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"催一下",
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"快点",
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"什么时候能好",
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"做完了吗",
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]
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if customer_text:
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prompt += f"\n客户说：{customer_text}\n"
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image_url = extract_image_url(customer_text)
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price_keywords = ["多少钱", "多少", "价格", "几块", "怎么收费", "报个价"]
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size_keywords = [
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"尺寸",
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"比例",
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"宽",
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"高",
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"米",
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"厘米",
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"mm",
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"cm",
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"横版",
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"竖版",
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"2米",
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"3米",
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"改成",
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"做成",
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]
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has_size_change = any(kw in customer_text.lower() for kw in [k.lower() for k in size_keywords])
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if shop_type == "gemini_api":
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prompt += "\n【Gemini API 店铺】客户问账号/pro/续费/套餐等，按 API 客服自然回复，不要求发图。"
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elif image_url:
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prompt += "\n客户在继续发图阶段：先确认“已收图”，并引导客户把图和要求一次发完；等客户明确“发完了/统一报价”后再统一报价。"
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elif any(kw in customer_text for kw in price_keywords):
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last_url = extract_image_url(msg_content)
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if last_url:
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prompt += "\n客户在询问价格：若客户已确认发完，则给总报价；若还在发图，先引导发完后统一报价。"
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else:
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prompt += "\n客户在询问价格但未发图：先简短承接（如“在看呢/收到”），不要机械连发；再自然引导对方发图。"
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if has_size_change:
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prompt += (
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"\n⚠️ 尺寸改动场景：优先判断图片主体是否会被拉伸变形，"
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"不是只看整张图宽高比。若会变形，要先提示“需要补图/扩边”，再给报价。"
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)
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elif has_size_change:
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prompt += (
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"\n客户在改尺寸/改比例：先按主体比例判断是否会变形，"
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"不是只看整图比例。若目标尺寸会拉伸主体，先明确说明要补图（如上下补图/扩边）再报价。"
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)
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elif any(kw in customer_text for kw in progress_keywords):
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if order_unpaid:
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prompt += "\n⚠️【订单未付款】客户问安排进度，但订单还未付款。自然告知拍下付款后马上安排即可。"
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elif order_paid:
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prompt += "\n客户催单，订单已付款，自然回复在做了/快了之类。"
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else:
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prompt += "\n客户催单，查询当前处理状态后自然回复。"
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elif any(kw in customer_text for kw in ["贵", "有点贵", "太贵", "算了", "便宜点", "少点", "打折", "贵哦"]):
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prompt += "\n⚠️【客户嫌贵】客户已表达价格顾虑或要放弃。禁止追问「什么问题」「说清楚点」。\n→ 第一步：直接让价一次（如原价 20→15），话术自然。\n→ 第二步：如果让价后客户还是嫌贵，引导客户自己去注册星绘平台：\n - 每个话术都必须带网址 xinhui.cloud\n - 强调「自己去弄」「自己操作」「自己下单」\n - 示例：「嫌贵就去 xinhui.cloud 注册个号，自己有余额可以弄」「xinhui.cloud 去注册下，新用户送体验金，自己弄便宜」\n - 语气直接，让客户自己去操作」"
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elif any(kw in customer_text for kw in ["擦边", "黄色", "色情", "大尺度", "性感图", "露点", "半裸"]):
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prompt += "\n⚠️【拒绝】客户询问擦边/黄色/敏感内容。直接拒绝，不接单，不说「发图来看看」。自然回复如：这类不做/不接/做不了。"
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else:
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prompt += "\n根据客户说的内容自然回应，像真人聊天，不要套模板。"
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if has_order:
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order = parse_order_info(order_block)
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order_instruction = build_order_instruction(order.get("pay_status", ""), order.get("order_status", ""))
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if customer_text:
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if not order_unpaid:
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prompt += f"\n\n【背景参考-订单通知】{order_instruction}"
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else:
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prompt += f"\n\n{order_instruction}"
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if not customer_text and not has_order:
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prompt += f"\n消息内容: {msg_content}\n请按工作流规则回复。"
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return prompt
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@@ -73,6 +73,8 @@ from core.batch_quote_helpers import (
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calc_requirement_surcharge,
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prepare_batch_intake,
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)
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from core.prompt_builder import build_prompt as build_agent_prompt, split_customer_text
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from core.image_workflow_router import handle_image_workflow as route_image_workflow
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load_dotenv()
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@@ -1777,215 +1779,25 @@ class CustomerServiceAgent:
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self._finalize_batch_state(state, message.from_id, final_price=bundle_price)
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return {"reply": reply_text, "need_transfer": False}
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def _split_customer_text(self, msg: str) -> tuple:
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"""
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把混合消息拆分为（客户真实文字, 系统订单块）。
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平台有时把客户文字和系统订单通知拼在同一条消息里。
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"""
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import re
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# 找到系统订单块的起始位置
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order_marker = re.search(r'\[系统订单信息\]|\[系统通知\]', msg)
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if order_marker:
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customer_text = msg[:order_marker.start()].strip()
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order_block = msg[order_marker.start():].strip()
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else:
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customer_text = msg.strip()
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order_block = ""
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return customer_text, order_block
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_split_customer_text = staticmethod(split_customer_text)
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def _build_prompt(self, message: CustomerMessage, state: ConversationState) -> str:
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"""构建提示词"""
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msg_content = message.msg
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stage_info = f"【当前阶段】{state.stage}"
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# 拆分：客户文字 vs 系统订单块
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customer_text, order_block = self._split_customer_text(msg_content)
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has_order = bool(order_block)
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if has_order:
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order = parse_order_info(order_block)
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if order.get('order_id'):
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state.last_order_id = order['order_id']
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stage_info += f"\n【订单号】{order['order_id']}"
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if order.get('order_status'):
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state.order_status = order['order_status']
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stage_info += f"\n【订单状态】{order['order_status']}"
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if order.get('pay_status'):
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stage_info += f"\n【支付状态】{order['pay_status']}"
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if order.get('amount'):
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stage_info += f"\n【订单金额】{order['amount']}元"
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if order.get('quantity'):
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stage_info += f"\n【数量】{order['quantity']}件"
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if order.get('order_time'):
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stage_info += f"\n【下单时间】{order['order_time']}"
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if order.get('buyer_note'):
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stage_info += f"\n【买家备注】{order['buyer_note']}"
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if state.discount_count > 0:
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stage_info += f"\n【客户压价次数】{state.discount_count}"
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# 店铺类型：不同店铺不同回复策略
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shop_type = _get_shop_type(message.acc_id or "", message.goods_name or "")
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shop_hint = ""
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try:
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from config.config import CONFIG_DIR
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import json
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cfg_path = CONFIG_DIR / "shop_prompts.json"
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if cfg_path.exists():
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with open(cfg_path, "r", encoding="utf-8") as f:
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cfg = json.load(f)
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hints = cfg.get("type_hints", {})
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shop_hint = hints.get(shop_type, "")
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if not shop_hint and message.acc_id:
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sh = cfg.get("shops", {}).get(message.acc_id, {})
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shop_hint = sh.get("hint", "")
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except Exception:
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pass
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prompt = f"""收到新消息：
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{stage_info}
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发送者: {message.from_name} ({message.from_id})
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"""
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if message.goods_name:
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prompt += f"商品名称: {message.goods_name}\n"
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if shop_hint:
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prompt += f"\n{shop_hint}\n"
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# ── 优先处理客户真实问题 ──
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# ── 判断订单付款状态（供后续逻辑使用）──
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order_paid = False
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order_unpaid = False
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if has_order:
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order = parse_order_info(order_block)
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paid_kws = ["等待发货", "已付款", "付款成功", "买家已付款"]
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unpaid_kws = ["等待买家付款", "待付款", "未付款"]
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ps = order.get('pay_status', '')
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os_ = order.get('order_status', '')
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if any(kw in ps or kw in os_ for kw in paid_kws):
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order_paid = True
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elif any(kw in ps or kw in os_ for kw in unpaid_kws):
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order_unpaid = True
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# ── 催单/进度询问关键词 ──
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progress_keywords = [
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"安排了吗", "安排好了吗", "好了吗", "做了吗", "做好了吗",
|
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"弄好了吗", "好了没", "做了没", "什么时候好", "多久好",
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"进度", "催一下", "快点", "什么时候能好", "做完了吗",
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]
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if customer_text:
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prompt += f"\n客户说：{customer_text}\n"
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image_url = self._extract_image_url(customer_text)
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price_keywords = ["多少钱", "多少", "价格", "几块", "怎么收费", "报个价"]
|
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size_keywords = [
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"尺寸", "比例", "宽", "高", "米", "厘米", "mm", "cm",
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"横版", "竖版", "2米", "3米", "改成", "做成",
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]
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has_size_change = any(kw in customer_text.lower() for kw in [k.lower() for k in size_keywords])
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# gemini_api 店铺：不触发找图流程，按 API 客服回复
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if shop_type == "gemini_api":
|
||||
prompt += "\n【Gemini API 店铺】客户问账号/pro/续费/套餐等，按 API 客服自然回复，不要求发图。"
|
||||
elif image_url:
|
||||
prompt += "\n客户在继续发图阶段：先确认“已收图”，并引导客户把图和要求一次发完；等客户明确“发完了/统一报价”后再统一报价。"
|
||||
elif any(kw in customer_text for kw in price_keywords):
|
||||
last_url = self._extract_image_url(msg_content)
|
||||
if last_url:
|
||||
prompt += "\n客户在询问价格：若客户已确认发完，则给总报价；若还在发图，先引导发完后统一报价。"
|
||||
else:
|
||||
prompt += "\n客户在询问价格但未发图：先简短承接（如“在看呢/收到”），不要机械连发；再自然引导对方发图。"
|
||||
if has_size_change:
|
||||
prompt += (
|
||||
"\n⚠️ 尺寸改动场景：优先判断图片主体是否会被拉伸变形，"
|
||||
"不是只看整张图宽高比。若会变形，要先提示“需要补图/扩边”，再给报价。"
|
||||
return build_agent_prompt(
|
||||
message=message,
|
||||
state=state,
|
||||
extract_image_url=self._extract_image_url,
|
||||
shop_type_resolver=_get_shop_type,
|
||||
parse_order_info=parse_order_info,
|
||||
build_order_instruction=build_order_instruction,
|
||||
)
|
||||
elif has_size_change:
|
||||
prompt += (
|
||||
"\n客户在改尺寸/改比例：先按主体比例判断是否会变形，"
|
||||
"不是只看整图比例。若目标尺寸会拉伸主体，先明确说明要补图（如上下补图/扩边）再报价。"
|
||||
)
|
||||
elif any(kw in customer_text for kw in progress_keywords):
|
||||
# 客户问进度/催单，必须先核查付款状态
|
||||
if order_unpaid:
|
||||
prompt += "\n⚠️【订单未付款】客户问安排进度，但订单还未付款。自然告知拍下付款后马上安排即可。"
|
||||
elif order_paid:
|
||||
prompt += "\n客户催单，订单已付款，自然回复在做了/快了之类。"
|
||||
else:
|
||||
prompt += "\n客户催单，查询当前处理状态后自然回复。"
|
||||
elif any(kw in customer_text for kw in ["贵", "有点贵", "太贵", "算了", "便宜点", "少点", "打折", "贵哦"]):
|
||||
# 客户嫌贵/要放弃 → 直接让价一次，不问「什么问题」
|
||||
prompt += "\n⚠️【客户嫌贵】客户已表达价格顾虑或要放弃。禁止追问「什么问题」「说清楚点」。\n→ 第一步：直接让价一次（如原价 20→15），话术自然。\n→ 第二步：如果让价后客户还是嫌贵，引导客户自己去注册星绘平台：\n - 每个话术都必须带网址 xinhui.cloud\n - 强调「自己去弄」「自己操作」「自己下单」\n - 示例：「嫌贵就去 xinhui.cloud 注册个号，自己有余额可以弄」「xinhui.cloud 去注册下，新用户送体验金，自己弄便宜」\n - 语气直接，让客户自己去操作」"
|
||||
elif any(kw in customer_text for kw in ["擦边", "黄色", "色情", "大尺度", "性感图", "露点", "半裸"]):
|
||||
# 客户问擦边/黄色内容 → 直接拒绝，不说「发图来看看」
|
||||
prompt += "\n⚠️【拒绝】客户询问擦边/黄色/敏感内容。直接拒绝，不接单，不说「发图来看看」。自然回复如：这类不做/不接/做不了。"
|
||||
else:
|
||||
prompt += "\n根据客户说的内容自然回应，像真人聊天，不要套模板。"
|
||||
|
||||
# ── 附加订单信息（不覆盖客户问题的优先级）──
|
||||
if has_order:
|
||||
order = parse_order_info(order_block)
|
||||
order_instruction = build_order_instruction(
|
||||
order.get('pay_status', ''),
|
||||
order.get('order_status', '')
|
||||
)
|
||||
if customer_text:
|
||||
if not order_unpaid:
|
||||
# 未付款情况已在上面明确处理，不重复添加背景
|
||||
prompt += f"\n\n【背景参考-订单通知】{order_instruction}"
|
||||
else:
|
||||
# 纯系统通知，没有客户文字
|
||||
prompt += f"\n\n{order_instruction}"
|
||||
|
||||
if not customer_text and not has_order:
|
||||
prompt += f"\n消息内容: {msg_content}\n请按工作流规则回复。"
|
||||
|
||||
return prompt
|
||||
|
||||
async def _handle_image_workflow(self, message: str, data: dict, image_urls: list) -> bool:
|
||||
"""处理图片工作流（根据客户说的话判断执行哪种工作流）"""
|
||||
if not image_urls:
|
||||
return False
|
||||
|
||||
workflow_type, confidence = self.workflow_router.detect_workflow(message)
|
||||
|
||||
customer_id = data.get('from_id')
|
||||
acc_id = data.get('acc_id', '')
|
||||
acc_type = data.get('acc_type', 'AliWorkbench')
|
||||
image_url = image_urls[0]
|
||||
|
||||
print(f"[Agent] 检测到工作流类型：{workflow_type} (置信度：{confidence})")
|
||||
|
||||
if workflow_type == "find_image":
|
||||
print(f"[Agent] 执行查找图片工作流 | 客户：{customer_id}")
|
||||
from core.workflow import workflow
|
||||
return await workflow.find_image_workflow(
|
||||
customer_id=customer_id,
|
||||
image_url=image_url,
|
||||
acc_id=acc_id,
|
||||
acc_type=acc_type
|
||||
return await route_image_workflow(
|
||||
workflow_router=self.workflow_router,
|
||||
message=message,
|
||||
data=data,
|
||||
image_urls=image_urls,
|
||||
)
|
||||
elif workflow_type == "process_image":
|
||||
print(f"[Agent] 执行处理图片工作流 | 客户：{customer_id}")
|
||||
from core.workflow import workflow
|
||||
return await workflow.process_image_workflow(
|
||||
customer_id=customer_id,
|
||||
image_url=image_url,
|
||||
acc_id=acc_id,
|
||||
acc_type=acc_type
|
||||
)
|
||||
elif workflow_type == "transfer_human":
|
||||
print(f"[Agent] 执行转人工派单工作流 | 客户：{customer_id}")
|
||||
from core.workflow import workflow
|
||||
return await workflow.transfer_to_designer_workflow(
|
||||
customer_id=customer_id,
|
||||
image_url=image_url,
|
||||
acc_id=acc_id,
|
||||
acc_type=acc_type,
|
||||
reason="客户主动要求转人工"
|
||||
)
|
||||
|
||||
return False
|
||||
|
||||
|
||||
async def test_agent():
|
||||
|
||||
Reference in New Issue
Block a user