fix: 更新LLMRequest类的任务名称确定逻辑,优先使用配置文件中的task_type和capabilities字段
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@@ -1,5 +1,5 @@
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[inner]
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version = "0.2.0"
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version = "0.2.1"
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# 配置文件版本号迭代规则同bot_config.toml
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#
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@@ -18,6 +18,28 @@ version = "0.2.0"
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# - 429频率限制:等待后重试,如果持续失败则切换Key
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# - 网络错误:短暂等待后重试,失败则切换Key
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# - 其他错误:按照正常重试机制处理
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#
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# === 任务类型和模型能力配置 ===
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# 为了提高任务分配的准确性和可维护性,现在支持明确配置模型的任务类型和能力:
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#
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# task_type(推荐配置):
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# - 明确指定模型主要用于什么任务
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# - 可选值:llm_normal, llm_reasoning, vision, embedding, speech
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# - 如果不配置,系统会根据capabilities或模型名称自动推断(不推荐)
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#
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# capabilities(推荐配置):
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# - 描述模型支持的所有能力
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# - 可选值:text, vision, embedding, speech, tool_calling, reasoning
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# - 支持多个能力的组合,如:["text", "vision"]
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#
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# 配置优先级:
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# 1. task_type(最高优先级,直接指定任务类型)
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# 2. capabilities(中等优先级,根据能力推断任务类型)
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# 3. 模型名称关键字(最低优先级,不推荐依赖)
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#
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# 向后兼容:
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# - 仍然支持 model_flags 字段,但建议迁移到 capabilities
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# - 未配置新字段时会自动回退到基于模型名称的推断
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[request_conf] # 请求配置(此配置项数值均为默认值,如想修改,请取消对应条目的注释)
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#max_retry = 2 # 最大重试次数(单个模型API调用失败,最多重试的次数)
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@@ -70,6 +92,13 @@ model_identifier = "deepseek-chat"
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name = "deepseek-v3"
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# API服务商名称(对应在api_providers中配置的服务商名称)
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api_provider = "DeepSeek"
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# 任务类型(推荐配置,明确指定模型主要用于什么任务)
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# 可选值:llm_normal, llm_reasoning, vision, embedding, speech
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# 如果不配置,系统会根据capabilities或模型名称自动推断
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task_type = "llm_normal"
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# 模型能力列表(推荐配置,描述模型支持的能力)
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# 可选值:text, vision, embedding, speech, tool_calling, reasoning
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capabilities = ["text", "tool_calling"]
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# 输入价格(用于API调用统计,单位:元/兆token)(可选,若无该字段,默认值为0)
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price_in = 2.0
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# 输出价格(用于API调用统计,单位:元/兆token)(可选,若无该字段,默认值为0)
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@@ -82,6 +111,10 @@ price_out = 8.0
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model_identifier = "deepseek-reasoner"
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name = "deepseek-r1"
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api_provider = "DeepSeek"
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# 推理模型的配置示例
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task_type = "llm_reasoning"
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capabilities = ["text", "tool_calling", "reasoning"]
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# 保留向后兼容的model_flags字段(已废弃,建议使用capabilities)
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model_flags = [ "text", "tool_calling", "reasoning",]
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price_in = 4.0
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price_out = 16.0
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@@ -90,6 +123,8 @@ price_out = 16.0
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model_identifier = "Pro/deepseek-ai/DeepSeek-V3"
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name = "siliconflow-deepseek-v3"
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api_provider = "SiliconFlow"
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task_type = "llm_normal"
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capabilities = ["text", "tool_calling"]
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price_in = 2.0
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price_out = 8.0
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@@ -97,6 +132,8 @@ price_out = 8.0
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model_identifier = "Pro/deepseek-ai/DeepSeek-R1"
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name = "siliconflow-deepseek-r1"
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api_provider = "SiliconFlow"
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task_type = "llm_reasoning"
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capabilities = ["text", "tool_calling", "reasoning"]
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price_in = 4.0
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price_out = 16.0
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@@ -104,6 +141,8 @@ price_out = 16.0
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model_identifier = "Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"
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name = "deepseek-r1-distill-qwen-32b"
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api_provider = "SiliconFlow"
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task_type = "llm_reasoning"
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capabilities = ["text", "tool_calling", "reasoning"]
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price_in = 4.0
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price_out = 16.0
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@@ -111,6 +150,8 @@ price_out = 16.0
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model_identifier = "Qwen/Qwen3-8B"
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name = "qwen3-8b"
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api_provider = "SiliconFlow"
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task_type = "llm_normal"
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capabilities = ["text"]
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price_in = 0
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price_out = 0
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@@ -118,6 +159,8 @@ price_out = 0
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model_identifier = "Qwen/Qwen3-14B"
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name = "qwen3-14b"
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api_provider = "SiliconFlow"
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task_type = "llm_normal"
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capabilities = ["text", "tool_calling"]
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price_in = 0.5
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price_out = 2.0
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@@ -125,6 +168,8 @@ price_out = 2.0
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model_identifier = "Qwen/Qwen3-30B-A3B"
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name = "qwen3-30b"
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api_provider = "SiliconFlow"
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task_type = "llm_normal"
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capabilities = ["text", "tool_calling"]
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price_in = 0.7
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price_out = 2.8
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@@ -132,6 +177,10 @@ price_out = 2.8
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model_identifier = "Qwen/Qwen2.5-VL-72B-Instruct"
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name = "qwen2.5-vl-72b"
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api_provider = "SiliconFlow"
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# 视觉模型的配置示例
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task_type = "vision"
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capabilities = ["vision", "text"]
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# 保留向后兼容的model_flags字段(已废弃,建议使用capabilities)
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model_flags = [ "vision", "text",]
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price_in = 4.13
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price_out = 4.13
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@@ -140,6 +189,10 @@ price_out = 4.13
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model_identifier = "FunAudioLLM/SenseVoiceSmall"
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name = "sensevoice-small"
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api_provider = "SiliconFlow"
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# 语音模型的配置示例
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task_type = "speech"
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capabilities = ["speech"]
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# 保留向后兼容的model_flags字段(已废弃,建议使用capabilities)
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model_flags = [ "audio",]
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price_in = 0
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price_out = 0
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@@ -148,6 +201,10 @@ price_out = 0
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model_identifier = "BAAI/bge-m3"
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name = "bge-m3"
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api_provider = "SiliconFlow"
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# 嵌入模型的配置示例
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task_type = "embedding"
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capabilities = ["text", "embedding"]
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# 保留向后兼容的model_flags字段(已废弃,建议使用capabilities)
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model_flags = [ "text", "embedding",]
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price_in = 0
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price_out = 0
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