mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
synced 2026-07-21 22:53:56 +08:00
179 lines
7.0 KiB
Python
179 lines
7.0 KiB
Python
import uuid
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import re
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from typing import List, Dict
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from datetime import datetime
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class Message:
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def __init__(
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self,
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role: str,
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content: str = None,
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uniq_id: str = None,
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tool_calls=None,
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tool_call_id=None,
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is_temporary=False,
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):
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self.uniq_id = uniq_id if uniq_id is not None else str(uuid.uuid4())
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self.role = role
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self.content = content
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self.tool_calls = tool_calls
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self.tool_call_id = tool_call_id
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self.is_temporary = is_temporary # 标记临时消息(如工具调用提醒)
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class Dialogue:
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def __init__(self):
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self.dialogue: List[Message] = []
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# 获取当前时间
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self.current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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def put(self, message: Message):
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self.dialogue.append(message)
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def getMessages(self, m, dialogue):
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if m.tool_calls is not None:
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dialogue.append({"role": m.role, "tool_calls": m.tool_calls})
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elif m.role == "tool":
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dialogue.append(
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{
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"role": m.role,
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"tool_call_id": (
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str(uuid.uuid4()) if m.tool_call_id is None else m.tool_call_id
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),
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"content": m.content,
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}
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)
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else:
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dialogue.append({"role": m.role, "content": m.content})
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def get_llm_dialogue(self) -> List[Dict[str, str]]:
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# 直接调用get_llm_dialogue_with_memory,传入None作为memory_str
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# 这样确保说话人功能在所有调用路径下都生效
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return self.get_llm_dialogue_with_memory(None, None)
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def update_system_message(self, new_content: str):
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"""更新或添加系统消息"""
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# 查找第一个系统消息
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system_msg = next((msg for msg in self.dialogue if msg.role == "system"), None)
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if system_msg:
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system_msg.content = new_content
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else:
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self.put(Message(role="system", content=new_content))
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def _ensure_tool_calls_complete(self, messages: List[Message]) -> List[Message]:
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"""
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确保所有 tool_calls 都有对应的 tool 响应
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修复被打断导致的悬空 tool_calls,防止大模型 API 报 400 错误
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"""
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pending_tool_calls = set()
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result = []
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for msg in messages:
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result.append(msg)
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if msg.role == "assistant" and msg.tool_calls:
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for tc in msg.tool_calls:
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tc_id = tc.get("id") if isinstance(tc, dict) else getattr(tc, "id", None)
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if tc_id:
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pending_tool_calls.add(tc_id)
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elif msg.role == "tool" and msg.tool_call_id:
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pending_tool_calls.discard(msg.tool_call_id)
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for missing_id in pending_tool_calls:
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dummy_tool_msg = Message(
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role="tool",
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content='{"status": "interrupted", "message": "动作已取消/被打断"}',
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tool_call_id=missing_id
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)
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result.append(dummy_tool_msg)
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return result
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def get_llm_dialogue_with_memory(
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self, memory_str: str = None, voiceprint_config: dict = None,
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current_speaker: str = None,
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) -> List[Dict[str, str]]:
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# 构建对话
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dialogue = []
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# 添加系统提示和记忆
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system_message = next(
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(msg for msg in self.dialogue if msg.role == "system"), None
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)
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if system_message:
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# 以 <context> 为分界点,拆分静态 system prompt 和动态上下文
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# 静态部分(规则、身份等)保持不变,可命中前缀缓存
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# 动态部分(时间、天气、记忆等)作为第二条 system 消息,保持 system 权威性
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full_prompt = system_message.content
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context_match = re.search(r"<context>", full_prompt)
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if context_match:
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static_part = full_prompt[:context_match.start()]
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dynamic_part = full_prompt[context_match.start():]
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else:
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static_part = full_prompt
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dynamic_part = ""
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# 第一段:静态 system prompt(前缀缓存可命中)
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dialogue.append({"role": "system", "content": static_part})
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# 第二段:few-shot 示例(会话内不变,也是缓存前缀的一部分)
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non_system_messages = [m for m in self.dialogue if m.role != "system"]
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fewshot_messages = [m for m in non_system_messages if m.is_temporary]
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complete_fewshot = self._ensure_tool_calls_complete(fewshot_messages)
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for m in complete_fewshot:
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self.getMessages(m, dialogue)
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# 第三段:动态上下文 system prompt(时间、记忆、说话人等)
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# 保持 system 角色以确保模型权威性,不降级为 user
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if system_message and dynamic_part:
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# 替换时间占位符
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dynamic_part = dynamic_part.replace(
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"{{current_time}}", datetime.now().strftime("%H:%M")
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)
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# 填充记忆
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if memory_str is not None:
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dynamic_part = re.sub(
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r"<memory>.*?</memory>",
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f"<memory>\n{memory_str}\n</memory>",
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dynamic_part,
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flags=re.DOTALL,
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)
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# 追加说话人信息
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try:
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current_speaker_name = (current_speaker or "").strip()
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# 仅在本轮注入了有效身份时才输出 speakers_info,避免列表里的名字每轮
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# 重复出现诱导模型反复称呼;后续轮不再注入身份,靠对话历史首轮保留
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if current_speaker_name and current_speaker_name != "未知说话人":
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speakers = voiceprint_config.get("speakers", [])
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dynamic_part += "\n<speakers_info>"
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dynamic_part += f"\n当前说话人:{current_speaker_name}"
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for speaker_str in speakers:
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try:
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parts = speaker_str.split(",", 2)
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if len(parts) >= 2:
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name = parts[1].strip()
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description = (
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parts[2].strip() if len(parts) >= 3 else ""
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)
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dynamic_part += f"\n- {name}:{description}"
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except:
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pass
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dynamic_part += "\n</speakers_info>"
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except:
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pass
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dialogue.append({"role": "system", "content": dynamic_part})
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# 第四段:实际对话历史(不含 few-shot)
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actual_messages = [m for m in non_system_messages if not m.is_temporary]
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complete_actual = self._ensure_tool_calls_complete(actual_messages)
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for m in complete_actual:
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self.getMessages(m, dialogue)
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return dialogue
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