diff --git a/main/xiaozhi-server/agent-base-prompt.txt b/main/xiaozhi-server/agent-base-prompt.txt
index 7b54792c..7c6f84b7 100644
--- a/main/xiaozhi-server/agent-base-prompt.txt
+++ b/main/xiaozhi-server/agent-base-prompt.txt
@@ -65,7 +65,7 @@ Calling unnecessarily is also wrong: User asks ”明天天气” → you call g
For the input format `{"speaker":"...", "content":"..."}` (speaker = speaker name, content = text):
-1. [Identity known] When `speaker` is a specific name, identity has been recognized. On the first turn you must address them naturally and adjust your response style based on their history.
+1. [Identity known] When `speaker` is a specific name, identity has been recognized — remember who they are. Do not start every reply by addressing them by name; get straight to the content (a natural greeting by name once, at the very start of a conversation, is fine). If they ask about their identity (e.g. "你知道我是谁吗", "还记得我吗"), answer truthfully using their recognized name.
2. [Identity unknown] When `speaker` is `未知说话人`, the system failed to identify the voice. You must NEVER mention the data inside the `speakers_info` tag to the user. Judge from context whether the speaker is the owner or the owner's friend, and keep the conversation natural.
diff --git a/main/xiaozhi-server/core/connection.py b/main/xiaozhi-server/core/connection.py
index fcf5183b..e7b853d3 100644
--- a/main/xiaozhi-server/core/connection.py
+++ b/main/xiaozhi-server/core/connection.py
@@ -159,6 +159,8 @@ class ConnectionHandler:
self.asr_audio = [] # 存储PCM帧列表，供VAD和ASR共享
self.asr_audio_queue = queue.Queue()
self.current_speaker = None # 存储当前说话人
+ self.introduced_speakers = set() # 已"首次引入"的说话人，控制只在首轮带名字
+ self.system_introduced_speakers = set() # 已在 system 注入过身份的说话人，控制 system 身份只首轮出现
# llm相关变量
self.dialogue = Dialogue()
@@ -1120,12 +1122,20 @@ class ConnectionHandler:
)
memory_str = future.result()
+ # 仅在该说话人首次出现时把身份注入 system，之后靠对话历史首轮保留，
+ # 避免每轮在 system 重复出现名字诱导模型反复称呼
+ speaker_for_system = None
+ cs = (self.current_speaker or "").strip()
+ if cs and cs != "未知说话人" and cs not in self.system_introduced_speakers:
+ self.system_introduced_speakers.add(cs)
+ speaker_for_system = cs
+
if self.intent_type == "function_call" and functions is not None:
# 使用支持functions的streaming接口
llm_responses = self.llm.response_with_functions(
self.session_id,
self.dialogue.get_llm_dialogue_with_memory(
- memory_str, self.config.get("voiceprint", {})
+ memory_str, self.config.get("voiceprint", {}), speaker_for_system
),
functions=functions,
)
@@ -1133,7 +1143,7 @@ class ConnectionHandler:
llm_responses = self.llm.response(
self.session_id,
self.dialogue.get_llm_dialogue_with_memory(
- memory_str, self.config.get("voiceprint", {})
+ memory_str, self.config.get("voiceprint", {}), speaker_for_system
),
)
except Exception as e:
diff --git a/main/xiaozhi-server/core/handle/receiveAudioHandle.py b/main/xiaozhi-server/core/handle/receiveAudioHandle.py
index 63a9f610..504669b8 100644
--- a/main/xiaozhi-server/core/handle/receiveAudioHandle.py
+++ b/main/xiaozhi-server/core/handle/receiveAudioHandle.py
@@ -43,7 +43,6 @@ async def resume_vad_detection(conn: "ConnectionHandler"):
async def startToChat(conn: "ConnectionHandler", text):
# 检查输入是否是JSON格式（包含说话人信息）
speaker_name = None
- language_tag = None
actual_text = text
try:
@@ -52,12 +51,16 @@ async def startToChat(conn: "ConnectionHandler", text):
data = json.loads(text)
if "speaker" in data and "content" in data:
speaker_name = data["speaker"]
- language_tag = data["language"]
- actual_text = data["content"]
+ actual_content = data["content"]
conn.logger.bind(tag=TAG).info(f"解析到说话人信息: {speaker_name}")
- # 直接使用JSON格式的文本，不解析
- actual_text = text
+ # 仅在该说话人首次出现时保留 {"speaker":...} JSON，让模型自然称呼一次；
+ # 后续轮降为纯文本，避免每轮重复出现名字诱导模型反复称呼
+ if speaker_name not in conn.introduced_speakers:
+ conn.introduced_speakers.add(speaker_name)
+ actual_text = text
+ else:
+ actual_text = actual_content
except (json.JSONDecodeError, KeyError):
# 如果解析失败，继续使用原始文本
pass
diff --git a/main/xiaozhi-server/core/providers/memory/powermem/powermem.py b/main/xiaozhi-server/core/providers/memory/powermem/powermem.py
index 72d6526f..6c581058 100644
--- a/main/xiaozhi-server/core/providers/memory/powermem/powermem.py
+++ b/main/xiaozhi-server/core/providers/memory/powermem/powermem.py
@@ -43,11 +43,8 @@ class MemoryProvider(MemoryProviderBase):
self.memory_client = None
self.enable_user_profile = False
self.last_profile_content = "" # Cache for user profile from UserMemory
-
try:
- # Check if user profile mode is enabled
- self.enable_user_profile = config.get("enable_user_profile", False)
-
+ self.enable_user_profile = str(config.get("enable_user_profile", False)).lower() == 'true'
# Get configuration parameters
database_provider = config.get("database_provider", "sqlite")
llm_provider = config.get("llm_provider", "qwen")
diff --git a/main/xiaozhi-server/core/utils/dialogue.py b/main/xiaozhi-server/core/utils/dialogue.py
index 4039f01e..ccc1e2c2 100644
--- a/main/xiaozhi-server/core/utils/dialogue.py
+++ b/main/xiaozhi-server/core/utils/dialogue.py
@@ -92,7 +92,8 @@ class Dialogue:
return result
def get_llm_dialogue_with_memory(
- self, memory_str: str = None, voiceprint_config: dict = None
+ self, memory_str: str = None, voiceprint_config: dict = None,
+ current_speaker: str = None,
) -> List[Dict[str, str]]:
# 构建对话
dialogue = []
@@ -103,50 +104,31 @@ class Dialogue:
)
if system_message:
- # 以 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"", 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(
+ full_prompt = full_prompt.replace(
"{{current_time}}", datetime.now().strftime("%H:%M")
)
# 填充记忆
if memory_str is not None:
- dynamic_part = re.sub(
+ full_prompt = re.sub(
r".*?",
f"\n{memory_str}\n",
- dynamic_part,
+ full_prompt,
flags=re.DOTALL,
)
# 追加说话人信息
try:
- speakers = voiceprint_config.get("speakers", [])
- if speakers:
- dynamic_part += "\n"
+ 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", [])
+ speakers_info = "\n"
+ speakers_info += f"\n当前说话人：{current_speaker_name}"
for speaker_str in speakers:
try:
parts = speaker_str.split(",", 2)
@@ -155,16 +137,24 @@ class Dialogue:
description = (
parts[2].strip() if len(parts) >= 3 else ""
)
- dynamic_part += f"\n- {name}：{description}"
+ speakers_info += f"\n- {name}：{description}"
except:
pass
- dynamic_part += "\n"
+ speakers_info += "\n"
+ full_prompt += speakers_info
except:
pass
- dialogue.append({"role": "system", "content": dynamic_part})
+ dialogue.append({"role": "system", "content": full_prompt})
- # 第四段：实际对话历史（不含 few-shot）
+ # 第二段：few-shot 示例（会话内不变）
+ 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：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: