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xiaozhi-esp32-server/main/xiaozhi-server/core/utils/dialogue.py
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DaGou12138 3b6e8f0e4b fix:
1.优化声纹称呼人提示词和注入逻辑,减少次次都称呼的频率
2026-07-08 16:14:10 +08:00

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