[inner] version = "0.1.1" # 配置文件版本号迭代规则同bot_config.toml [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) #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) #timeout = 10 # API调用的超时时长(超过这个时长,本次请求将被视为“请求超时”,单位:秒) #retry_interval = 10 # 重试间隔(如果API调用失败,重试的间隔时间,单位:秒) #default_temperature = 0.7 # 默认的温度(如果bot_config.toml中没有设置temperature参数,默认使用这个值) #default_max_tokens = 1024 # 默认的最大输出token数(如果bot_config.toml中没有设置max_tokens参数,默认使用这个值) [[api_providers]] # API服务提供商(可以配置多个) name = "DeepSeek" # API服务商名称(可随意命名,在models的api-provider中需使用这个命名) base_url = "https://api.deepseek.cn" # API服务商的BaseURL key = "******" # API Key (可选,默认为None) client_type = "openai" # 请求客户端(可选,默认值为"openai",使用gimini等Google系模型时请配置为"google") #[[api_providers]] # 特殊:Google的Gimini使用特殊API,与OpenAI格式不兼容,需要配置client为"google" #name = "Google" #base_url = "https://api.google.com" #key = "******" #client_type = "google" # #[[api_providers]] #name = "SiliconFlow" #base_url = "https://api.siliconflow.cn" #key = "******" # #[[api_providers]] #name = "LocalHost" #base_url = "https://localhost:8888" #key = "lm-studio" [[models]] # 模型(可以配置多个) # 模型标识符(API服务商提供的模型标识符) model_identifier = "deepseek-chat" # 模型名称(可随意命名,在bot_config.toml中需使用这个命名) #(可选,若无该字段,则将自动使用model_identifier填充) name = "deepseek-v3" # API服务商名称(对应在api_providers中配置的服务商名称) api_provider = "DeepSeek" # 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) price_in = 2.0 # 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) price_out = 8.0 # 强制流式输出模式(若模型不支持非流式输出,请取消该注释,启用强制流式输出) #(可选,若无该字段,默认值为false) #force_stream_mode = true [[models]] model_identifier = "deepseek-reasoner" name = "deepseek-r1" api_provider = "DeepSeek" model_flags = [ "text", "tool_calling", "reasoning",] price_in = 4.0 price_out = 16.0 [[models]] model_identifier = "Pro/deepseek-ai/DeepSeek-V3" name = "siliconflow-deepseek-v3" api_provider = "SiliconFlow" price_in = 2.0 price_out = 8.0 [[models]] model_identifier = "Pro/deepseek-ai/DeepSeek-R1" name = "siliconflow-deepseek-r1" api_provider = "SiliconFlow" price_in = 4.0 price_out = 16.0 [[models]] model_identifier = "Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B" name = "deepseek-r1-distill-qwen-32b" api_provider = "SiliconFlow" price_in = 4.0 price_out = 16.0 [[models]] model_identifier = "Qwen/Qwen3-8B" name = "qwen3-8b" api_provider = "SiliconFlow" price_in = 0 price_out = 0 [[models]] model_identifier = "Qwen/Qwen3-14B" name = "qwen3-14b" api_provider = "SiliconFlow" price_in = 0.5 price_out = 2.0 [[models]] model_identifier = "Qwen/Qwen3-30B-A3B" name = "qwen3-30b" api_provider = "SiliconFlow" price_in = 0.7 price_out = 2.8 [[models]] model_identifier = "Qwen/Qwen2.5-VL-72B-Instruct" name = "qwen2.5-vl-72b" api_provider = "SiliconFlow" model_flags = [ "vision", "text",] price_in = 4.13 price_out = 4.13 [[models]] model_identifier = "FunAudioLLM/SenseVoiceSmall" name = "sensevoice-small" api_provider = "SiliconFlow" model_flags = [ "audio",] price_in = 0 price_out = 0 [[models]] model_identifier = "BAAI/bge-m3" name = "bge-m3" api_provider = "SiliconFlow" model_flags = [ "text", "embedding",] price_in = 0 price_out = 0 [task_model_usage] #llm_reasoning = {model="deepseek-r1", temperature=0.8, max_tokens=1024, max_retry=0} #llm_normal = {model="deepseek-r1", max_tokens=1024, max_retry=0} #embedding = "siliconflow-bge-m3" #schedule = [ # "deepseek-v3", # "deepseek-r1", #]