fix: 更新模型配置和环境变量,调整版本号和模型参数
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@@ -229,120 +229,84 @@ show_prompt = false # 是否显示prompt
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[model]
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model_max_output_length = 1024 # 模型单次返回的最大token数
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model_max_output_length = 800 # 模型单次返回的最大token数
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#------------必填:组件模型------------
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#------------模型任务配置------------
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# 所有模型名称需要对应 model_config.toml 中配置的模型名称
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[model.utils] # 在麦麦的一些组件中使用的模型,例如表情包模块,取名模块,关系模块,是麦麦必须的模型
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name = "Pro/deepseek-ai/DeepSeek-V3"
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provider = "SILICONFLOW"
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pri_in = 2 #模型的输入价格(非必填,可以记录消耗)
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pri_out = 8 #模型的输出价格(非必填,可以记录消耗)
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#默认temp 0.2 如果你使用的是老V3或者其他模型,请自己修改temp参数
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temp = 0.2 #模型的温度,新V3建议0.1-0.3
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model_name = "siliconflow-deepseek-v3" # 对应 model_config.toml 中的模型名称
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temperature = 0.2 # 模型温度,新V3建议0.1-0.3
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max_tokens = 800 # 最大输出token数
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[model.utils_small] # 在麦麦的一些组件中使用的小模型,消耗量较大,建议使用速度较快的小模型
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# 强烈建议使用免费的小模型
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name = "Qwen/Qwen3-8B"
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provider = "SILICONFLOW"
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pri_in = 0
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pri_out = 0
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temp = 0.7
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model_name = "qwen3-8b" # 对应 model_config.toml 中的模型名称
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temperature = 0.7
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max_tokens = 800
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enable_thinking = false # 是否启用思考
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[model.replyer_1] # 首要回复模型,还用于表达器和表达方式学习
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name = "Pro/deepseek-ai/DeepSeek-V3"
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provider = "SILICONFLOW"
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pri_in = 2 #模型的输入价格(非必填,可以记录消耗)
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pri_out = 8 #模型的输出价格(非必填,可以记录消耗)
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#默认temp 0.2 如果你使用的是老V3或者其他模型,请自己修改temp参数
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temp = 0.2 #模型的温度,新V3建议0.1-0.3
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model_name = "siliconflow-deepseek-v3" # 对应 model_config.toml 中的模型名称
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temperature = 0.2 # 模型温度,新V3建议0.1-0.3
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max_tokens = 800
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[model.replyer_2] # 次要回复模型
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name = "Pro/deepseek-ai/DeepSeek-V3"
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provider = "SILICONFLOW"
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pri_in = 2 #模型的输入价格(非必填,可以记录消耗)
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pri_out = 8 #模型的输出价格(非必填,可以记录消耗)
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#默认temp 0.2 如果你使用的是老V3或者其他模型,请自己修改temp参数
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temp = 0.2 #模型的温度,新V3建议0.1-0.3
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model_name = "siliconflow-deepseek-r1" # 对应 model_config.toml 中的模型名称
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temperature = 0.7 # 模型温度
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max_tokens = 800
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[model.planner] #决策:负责决定麦麦该做什么的模型
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name = "Pro/deepseek-ai/DeepSeek-V3"
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provider = "SILICONFLOW"
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pri_in = 2
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pri_out = 8
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temp = 0.3
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model_name = "siliconflow-deepseek-v3" # 对应 model_config.toml 中的模型名称
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temperature = 0.3
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max_tokens = 800
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[model.emotion] #负责麦麦的情绪变化
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name = "Pro/deepseek-ai/DeepSeek-V3"
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provider = "SILICONFLOW"
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pri_in = 2
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pri_out = 8
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temp = 0.3
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model_name = "siliconflow-deepseek-v3" # 对应 model_config.toml 中的模型名称
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temperature = 0.3
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max_tokens = 800
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[model.memory] # 记忆模型
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name = "Qwen/Qwen3-30B-A3B"
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provider = "SILICONFLOW"
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pri_in = 0.7
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pri_out = 2.8
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temp = 0.7
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model_name = "qwen3-30b" # 对应 model_config.toml 中的模型名称
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temperature = 0.7
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max_tokens = 800
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enable_thinking = false # 是否启用思考
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[model.vlm] # 图像识别模型
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name = "Pro/Qwen/Qwen2.5-VL-7B-Instruct"
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provider = "SILICONFLOW"
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pri_in = 0.35
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pri_out = 0.35
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model_name = "qwen2.5-vl-72b" # 对应 model_config.toml 中的模型名称
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max_tokens = 800
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[model.voice] # 语音识别模型
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name = "FunAudioLLM/SenseVoiceSmall"
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provider = "SILICONFLOW"
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pri_in = 0
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pri_out = 0
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model_name = "sensevoice-small" # 对应 model_config.toml 中的模型名称
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[model.tool_use] #工具调用模型,需要使用支持工具调用的模型
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name = "Qwen/Qwen3-14B"
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provider = "SILICONFLOW"
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pri_in = 0.5
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pri_out = 2
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temp = 0.7
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model_name = "qwen3-14b" # 对应 model_config.toml 中的模型名称
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temperature = 0.7
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max_tokens = 800
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enable_thinking = false # 是否启用思考(qwen3 only)
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#嵌入模型
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[model.embedding]
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name = "BAAI/bge-m3"
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provider = "SILICONFLOW"
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pri_in = 0
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pri_out = 0
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model_name = "bge-m3" # 对应 model_config.toml 中的模型名称
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#------------LPMM知识库模型------------
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[model.lpmm_entity_extract] # 实体提取模型
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name = "Pro/deepseek-ai/DeepSeek-V3"
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provider = "SILICONFLOW"
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pri_in = 2
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pri_out = 8
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temp = 0.2
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model_name = "siliconflow-deepseek-v3" # 对应 model_config.toml 中的模型名称
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temperature = 0.2
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max_tokens = 800
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[model.lpmm_rdf_build] # RDF构建模型
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name = "Pro/deepseek-ai/DeepSeek-V3"
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provider = "SILICONFLOW"
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pri_in = 2
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pri_out = 8
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temp = 0.2
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model_name = "siliconflow-deepseek-v3" # 对应 model_config.toml 中的模型名称
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temperature = 0.2
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max_tokens = 800
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[model.lpmm_qa] # 问答模型
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name = "Qwen/Qwen3-30B-A3B"
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provider = "SILICONFLOW"
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pri_in = 0.7
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pri_out = 2.8
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temp = 0.7
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model_name = "deepseek-r1-distill-qwen-32b" # 对应 model_config.toml 中的模型名称
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temperature = 0.7
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max_tokens = 800
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enable_thinking = false # 是否启用思考
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[maim_message]
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auth_token = [] # 认证令牌,用于API验证,为空则不启用验证
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# 以下项目若要使用需要打开use_custom,并单独配置maim_message的服务器
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