216 lines
10 KiB
Python
216 lines
10 KiB
Python
from __future__ import annotations
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from datetime import datetime
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from typing import TYPE_CHECKING, Optional
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if TYPE_CHECKING:
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from core.pydantic_ai_agent import AgentResponse, ConversationState, CustomerMessage, CustomerServiceAgent
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async def handle_find_image_batch_flow(
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agent: "CustomerServiceAgent",
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*,
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message: "CustomerMessage",
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state: "ConversationState",
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customer_text: str,
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shop_type: str,
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) -> Optional["AgentResponse"]:
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"""Handle find-image collecting/quote flow. Return response when handled."""
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from core.pydantic_ai_agent import AgentResponse, TRANSFER_MESSAGE
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if not (shop_type == "find_image" and agent._is_batch_quote_enabled(message.from_id, message.acc_id)):
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return None
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incoming_urls = agent._extract_image_urls(customer_text)
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text_without_urls = agent._strip_urls_from_text(customer_text)
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short_intent = agent._classify_short_customer_text(text_without_urls)
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if incoming_urls:
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is_related_followup = bool(text_without_urls and agent._is_related_image_followup_intent(text_without_urls))
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for u in incoming_urls:
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if u not in state.pending_image_urls:
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state.pending_image_urls.append(u)
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if text_without_urls:
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agent._append_requirement(state, text_without_urls)
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if is_related_followup:
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agent._append_requirement(state, "与上一张相关（截图/局部细节）")
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state.image_count = len(state.pending_image_urls)
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agent._refresh_quote_phase(state, "collecting")
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agent._sync_pending_quote_state(message.from_id, state)
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if agent._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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should_defer = agent._should_defer_batch_quote(state, mark_ready=True)
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agent._sync_pending_quote_state(message.from_id, state)
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if should_defer:
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defer_fallback = "图片和需求我都收齐了，我先整理下，马上给你报总价。"
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defer_reply = await agent._render_collection_reply_with_ai(
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message=message,
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state=state,
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scene="quote_defer_notice",
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intent_hint="确认已收齐图片与需求，先承接，告知稍后马上报价。",
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fallback=defer_fallback,
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)
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state.last_reply_at = datetime.now()
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print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {defer_reply}")
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return AgentResponse(reply=defer_reply, should_reply=True, need_transfer=False)
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quote_res = await agent._quote_pending_images(state, message)
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reply_text = agent._colloquialize_reply(quote_res.get("reply", ""))
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reply_text = await agent._rewrite_reply_with_ai(
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message=message,
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state=state,
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reply=reply_text,
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scene="batch_quote_reply",
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)
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need_transfer = bool(quote_res.get("need_transfer"))
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state.last_reply_at = datetime.now()
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print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {reply_text}")
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return AgentResponse(
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reply=reply_text,
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should_reply=not need_transfer,
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need_transfer=need_transfer,
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transfer_msg=TRANSFER_MESSAGE if need_transfer else "",
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)
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ack_fallback = "图片收到了，你有补充就继续发，我这边一起看。"
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ack_intent = (
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"告知图片已收到；如果客户继续发图就继续收，发完可统一报价。"
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if not is_related_followup
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else "告知这是和上一张相关的截图/局部图，已按同一需求一起处理。"
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)
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ack = await agent._render_collection_reply_with_ai(
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message=message,
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state=state,
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scene="collect_ack",
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intent_hint=ack_intent,
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fallback=ack_fallback,
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)
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state.last_reply_at = datetime.now()
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print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {ack}")
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return AgentResponse(reply=ack, should_reply=True, need_transfer=False)
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if not state.pending_image_urls:
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return None
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if text_without_urls:
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if short_intent == "finish_signal":
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agent._mark_quote_ready(state)
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elif short_intent == "progress_query":
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if state.quote_phase != "ready_to_quote":
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agent._refresh_quote_phase(state, "waiting_result")
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elif short_intent == "ack":
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if state.quote_phase != "ready_to_quote":
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agent._refresh_quote_phase(state, "collecting")
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else:
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agent._append_requirement(state, text_without_urls)
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agent._refresh_quote_phase(state, "collecting")
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agent._sync_pending_quote_state(message.from_id, state)
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if agent._is_find_image_not_edit_conflict(text_without_urls):
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clarify_fallback = "明白你是要找图，不是做图。你说下要找原图、同款还是高清版，我按这个给你找。"
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clarify = await agent._render_collection_reply_with_ai(
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message=message,
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state=state,
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scene="find_not_edit_clarify",
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intent_hint="确认客户要找图不是做图，并追问是找原图/同款/高清版。",
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fallback=clarify_fallback,
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)
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state.last_reply_at = datetime.now()
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print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {clarify}")
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return AgentResponse(reply=clarify, should_reply=True, need_transfer=False)
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if state.quote_phase == "ready_to_quote" and state.quote_ready_turns <= 0 and short_intent in {"progress_query", "ack", "finish_signal"}:
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quote_res = await agent._quote_pending_images(state, message)
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reply_text = agent._colloquialize_reply(quote_res.get("reply", ""))
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reply_text = await agent._rewrite_reply_with_ai(
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message=message,
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state=state,
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reply=reply_text,
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scene="batch_quote_reply",
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)
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need_transfer = bool(quote_res.get("need_transfer"))
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state.last_reply_at = datetime.now()
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print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {reply_text}")
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return AgentResponse(
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reply=reply_text,
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should_reply=not need_transfer,
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need_transfer=need_transfer,
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transfer_msg=TRANSFER_MESSAGE if need_transfer else "",
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)
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if short_intent == "progress_query" or agent._is_result_followup_query(text_without_urls):
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progress_fallback = "我这边在跟进了，一有结果马上发你。"
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progress = await agent._render_collection_reply_with_ai(
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message=message,
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state=state,
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scene="collect_progress",
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intent_hint="承接客户的进度/结果追问，简短说明正在跟进，有结果会第一时间回复。",
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fallback=progress_fallback,
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)
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state.last_reply_at = datetime.now()
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print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {progress}")
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return AgentResponse(reply=progress, should_reply=True, need_transfer=False)
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if agent._needs_clarification_in_collecting(text_without_urls):
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ask_fallback = "你再补一句具体要什么效果，我马上按你的要求来。"
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ask = await agent._render_collection_reply_with_ai(
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message=message,
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state=state,
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scene="collect_clarify",
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intent_hint="客户表达不清，礼貌请对方补充一句关键需求，不要机械，不要生硬。",
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fallback=ask_fallback,
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)
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state.last_reply_at = datetime.now()
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print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {ask}")
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return AgentResponse(reply=ask, should_reply=True, need_transfer=False)
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if agent._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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should_defer = agent._should_defer_batch_quote(state, mark_ready=True)
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agent._sync_pending_quote_state(message.from_id, state)
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if should_defer:
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defer_fallback = "收到，我先把这批图过一遍，马上给你总价。"
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defer_reply = await agent._render_collection_reply_with_ai(
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message=message,
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state=state,
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scene="quote_defer_notice",
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intent_hint="确认已收齐，先承接并告知稍后马上报价。",
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fallback=defer_fallback,
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)
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state.last_reply_at = datetime.now()
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print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {defer_reply}")
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return AgentResponse(reply=defer_reply, should_reply=True, need_transfer=False)
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quote_res = await agent._quote_pending_images(state, message)
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reply_text = agent._colloquialize_reply(quote_res.get("reply", ""))
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reply_text = await agent._rewrite_reply_with_ai(
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message=message,
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state=state,
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reply=reply_text,
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scene="batch_quote_reply",
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)
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need_transfer = bool(quote_res.get("need_transfer"))
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state.last_reply_at = datetime.now()
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print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {reply_text}")
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return AgentResponse(
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reply=reply_text,
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should_reply=not need_transfer,
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need_transfer=need_transfer,
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transfer_msg=TRANSFER_MESSAGE if need_transfer else "",
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)
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remind_fallback = "需求我记上了，你继续发图，或者让我直接给你报价都行。"
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remind = await agent._render_collection_reply_with_ai(
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message=message,
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state=state,
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scene="collect_remind",
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intent_hint="确认需求已记录，引导客户继续补图或直接让你报价。",
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fallback=remind_fallback,
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)
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state.last_reply_at = datetime.now()
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print(f"{agent.C_REPLY}[REPLY->CUSTOMER]{agent.C_RESET} {remind}")
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return AgentResponse(reply=remind, should_reply=True, need_transfer=False)
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