better 更好的llm使用统计
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@@ -128,52 +128,60 @@ enable = true
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#下面的模型若使用硅基流动则不需要更改,使用ds官方则改成.env.prod自定义的宏,使用自定义模型则选择定位相似的模型自己填写
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#推理模型:
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#推理模型
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[model.llm_reasoning] #回复模型1 主要回复模型
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name = "Pro/deepseek-ai/DeepSeek-R1"
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# name = "Qwen/QwQ-32B"
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provider = "SILICONFLOW"
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pri_in = 0 #模型的输入价格(非必填,可以记录消耗)
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pri_out = 0 #模型的输出价格(非必填,可以记录消耗)
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pri_in = 4 #模型的输入价格(非必填,可以记录消耗)
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pri_out = 16 #模型的输出价格(非必填,可以记录消耗)
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[model.llm_reasoning_minor] #回复模型3 次要回复模型
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name = "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"
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provider = "SILICONFLOW"
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pri_in = 1.26 #模型的输入价格(非必填,可以记录消耗)
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pri_out = 1.26 #模型的输出价格(非必填,可以记录消耗)
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#非推理模型
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[model.llm_normal] #V3 回复模型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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[model.llm_normal_minor] #V2.5
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name = "deepseek-ai/DeepSeek-V2.5"
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provider = "SILICONFLOW"
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[model.llm_emotion_judge] #主题判断 0.7/m
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[model.llm_emotion_judge] #表情包判断
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name = "Qwen/Qwen2.5-14B-Instruct"
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provider = "SILICONFLOW"
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pri_in = 0.7
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pri_out = 0.7
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[model.llm_topic_judge] #主题判断:建议使用qwen2.5 7b
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[model.llm_topic_judge] #记忆主题判断:建议使用qwen2.5 7b
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name = "Pro/Qwen/Qwen2.5-7B-Instruct"
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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.llm_summary_by_topic] #建议使用qwen2.5 32b 及以上
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[model.llm_summary_by_topic] #概括模型,建议使用qwen2.5 32b 及以上
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name = "Qwen/Qwen2.5-32B-Instruct"
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provider = "SILICONFLOW"
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pri_in = 0
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pri_out = 0
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pri_in = 1.26
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pri_out = 1.26
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[model.moderation] #内容审核 未启用
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[model.moderation] #内容审核,开发中
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name = ""
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provider = "SILICONFLOW"
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pri_in = 0
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pri_out = 0
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pri_in = 1.0
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pri_out = 2.0
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# 识图模型
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[model.vlm] #图像识别 0.35/m
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name = "Pro/Qwen/Qwen2-VL-7B-Instruct"
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[model.vlm] #图像识别
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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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#嵌入模型
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