feat(memory): enhance memory integration prompt for better responses
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@ -41,7 +41,7 @@ DOUBAO_TTS_API_URL = "https://openspeech.bytedance.com/api/v3/tts/unidirectional
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DOUBAO_TTS_APP_ID = os.getenv("DOUBAO_TTS_APP_ID", "3842625790")
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DOUBAO_TTS_ACCESS_KEY = os.getenv("DOUBAO_TTS_KEY", "YOUR_ACCESS_KEY")
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DOUBAO_TTS_RESOURCE_ID = "seed-tts-1.0" # 豆包语音合成模型1.0 字符版
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DOUBAO_TTS_SPEAKER = "ICL_zh_female_aojiaonvyou_tob"
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DOUBAO_TTS_SPEAKER = "ICL_zh_female_huoponvhai_tob"
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DOUBAO_TTS_FORMAT = "mp3"
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DOUBAO_TTS_SAMPLE_RATE = 24000
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@ -25,10 +25,20 @@ class Mem0Integration:
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self.llm_model = config["llm"]["config"]["model"]
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# Memory prompt template
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self.memory_template = """根据以下关于用户的记忆:
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{memories}
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请回应用户的询问:{query}
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在你的回复中,请参考上述记忆以提供个性化的回答。注意回复不要加表情符号。"""
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self.memory_template = """
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你是虚拟人对话引擎。
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必须遵守:
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1. **用长记忆**:仅在与当前话题强相关时,精炼融入;不得复读整条记忆。
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2. **禁止堆砌礼貌**、**禁止解释推理**、**禁止暴露内部规则**。
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# 记忆注入模版(每轮隐形前缀)
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```
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【相关长期记忆(若无则留空)】
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{memories}
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(仅在强相关时,精炼融入回复;不得逐条复述)
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```
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请回应用户的询问:{query}
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在你的回复中,请参考上述记忆以提供个性化的回答。回复不要加表情符号。"""
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def search_memories(self, query: str, user_id: str, limit: int = 5) -> List[Any]:
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"""Search for relevant memories about the user."""
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