mirror of
https://github.com/Zippland/Bubbles.git
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131 lines
4.4 KiB
Python
131 lines
4.4 KiB
Python
"""Chat fallback utilities for Function Call routing."""
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from __future__ import annotations
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import time
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from typing import Optional
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from commands.context import MessageContext
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def run_chat_fallback(ctx: MessageContext) -> bool:
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"""Send a conversational reply using the active chat model.
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This is used when no Function Call handler processes the message.
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Returns True if a reply was sent successfully.
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"""
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chat_model = getattr(ctx, "chat", None) or getattr(ctx.robot, "chat", None)
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if not chat_model:
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if ctx.logger:
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ctx.logger.error("聊天兜底失败：没有可用的 chat 模型")
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ctx.send_text("抱歉，我现在无法进行对话。")
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return False
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specific_max_history: Optional[int] = getattr(ctx, "specific_max_history", None)
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if getattr(ctx, "is_quoted_image", False):
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if not _handle_quoted_image(ctx, chat_model):
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return False
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return True
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prompt = _build_prompt(ctx)
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if ctx.logger:
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ctx.logger.info(f"闲聊兜底发送给 AI 的内容:\n{prompt}")
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try:
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answer = chat_model.get_answer(
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question=prompt,
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wxid=ctx.get_receiver(),
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specific_max_history=specific_max_history,
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)
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except Exception as exc: # pragma: no cover - safety net
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if ctx.logger:
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ctx.logger.error(f"闲聊兜底调用模型失败: {exc}")
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return False
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if not answer:
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if ctx.logger:
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ctx.logger.warning("闲聊兜底返回空响应")
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return False
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at_list = ctx.msg.sender if ctx.is_group else ""
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ctx.send_text(answer, at_list)
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return True
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def _build_prompt(ctx: MessageContext) -> str:
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sender_name = ctx.sender_name
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content = ctx.text or ""
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if ctx.robot and hasattr(ctx.robot, "xml_processor"):
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if ctx.is_group:
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msg_data = ctx.robot.xml_processor.extract_quoted_message(ctx.msg)
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formatted = ctx.robot.xml_processor.format_message_for_ai(msg_data, sender_name)
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else:
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msg_data = ctx.robot.xml_processor.extract_private_quoted_message(ctx.msg)
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formatted = ctx.robot.xml_processor.format_message_for_ai(msg_data, sender_name)
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if formatted:
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return formatted
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current_time = time.strftime("%H:%M", time.localtime())
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return f"[{current_time}] {sender_name}: {content or '[空内容]'}"
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def _handle_quoted_image(ctx: MessageContext, chat_model) -> bool:
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if ctx.logger:
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ctx.logger.info("检测到引用图片，尝试走模型图片理解能力")
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from ai_providers.ai_chatgpt import ChatGPT # 避免循环导入
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support_vision = False
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if isinstance(chat_model, ChatGPT):
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support_vision = getattr(chat_model, "support_vision", False)
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if not support_vision and hasattr(chat_model, "model"):
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model_name = getattr(chat_model, "model", "")
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support_vision = model_name in {"gpt-4.1-mini", "gpt-4o"} or "-vision" in model_name
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if not support_vision:
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ctx.send_text("当前模型不支持图片理解，请联系管理员配置支持视觉的模型。")
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return True
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import os
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temp_dir = "temp/image_cache"
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os.makedirs(temp_dir, exist_ok=True)
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try:
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image_path = ctx.wcf.download_image(
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id=ctx.quoted_msg_id,
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extra=ctx.quoted_image_extra,
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dir=temp_dir,
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timeout=30,
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)
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except Exception as exc: # pragma: no cover - IO 失败
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if ctx.logger:
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ctx.logger.error(f"图片下载失败: {exc}")
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ctx.send_text("抱歉，无法下载图片进行分析。")
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return True
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if not image_path or not os.path.exists(image_path):
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ctx.send_text("抱歉，无法下载图片进行分析。")
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return True
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prompt = ctx.text.strip() or "请详细描述这张图片"
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try:
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response = chat_model.get_image_description(image_path, prompt)
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ctx.send_text(response)
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except Exception as exc: # pragma: no cover - 模型异常
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if ctx.logger:
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ctx.logger.error(f"图片分析失败: {exc}")
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ctx.send_text(f"分析图片时出错: {exc}")
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finally:
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try:
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if os.path.exists(image_path):
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os.remove(image_path)
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except OSError:
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if ctx.logger:
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ctx.logger.warning(f"清理临时图片失败: {image_path}")
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return True
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