获取不同模型类型支持的指标列表

功能介绍

获取不同模型类型支持的指标列表接口用于获取服务模型类型对应支持的指标列表。

接口约束

• 区域限制：仅支持西南-贵阳一区域。
• API流量限制：所有用户对该API的总请求次数上限，1分钟内不超过1000次。
• 用户流量限制：单个用户对该API的请求次数上限，1分钟内不超过200次。
• 限流响应：超出限流阈值时，API将返回HTTP 429状态码（Too Many Requests）。
• 重试建议：遇到限流时，建议等待60秒后重试。

URI

GET /v1/{project_id}/maas/monitoring/generation-supported-metrics

请求参数

响应参数

状态码：200

状态码：400

请求示例

查询各类型模型支持的调用统计指标。

/v1/{project_id}/maas/monitoring/generation-supported-metrics

响应示例

状态码：200

成功响应。

[ {
  "type" : "Text Generation",
  "metrics" : [ "request_count", "succ_2xx_count", "error_count", "req_count4xx5xx", "error_rate", "total_token", "avg_total_token", "max_total_token", "p50_total_token", "p80_total_token", "p90_total_token", "p99_total_token", "prompt_token", "completion_token", "avg_prompt_token", "p50_prompt_token", "p80_prompt_token", "p90_prompt_token", "p99_prompt_token", "max_prompt_token", "avg_completion_token", "p50_completion_token", "p80_completion_token", "p90_completion_token", "p99_completion_token", "max_completion_token", "avg_latency", "rpm", "tpm", "avg_ttft", "p50_ttft", "p80_ttft", "p90_ttft", "p99_ttft", "max_ttft", "avg_tpot", "p50_tpot", "p80_tpot", "p90_tpot", "p99_tpot", "max_tpot", "cache_token", "cache_hit_ratio" ],
  "desc_zh" : "文本生成类模型",
  "desc_en" : "Text generation model"
}, {
  "type" : "Video Generation",
  "metrics" : [ "request_count", "succ_2xx_count", "error_count", "req_count4xx5xx", "error_rate", "total_token", "avg_total_token", "max_total_token", "p50_total_token", "p80_total_token", "p90_total_token", "p99_total_token", "completion_token", "avg_completion_token", "p50_completion_token", "p80_completion_token", "p90_completion_token", "p99_completion_token", "max_completion_token", "avg_generation_time", "rpm", "tpm" ],
  "desc_zh" : "视频生成类模型",
  "desc_en" : "Video generation model"
}, {
  "type" : "Image Generation",
  "metrics" : [ "request_count", "succ_2xx_count", "error_count", "req_count4xx5xx", "error_rate", "avg_latency", "avg_generation_time" ],
  "desc_zh" : "图像生成类模型",
  "desc_en" : "Image generation model"
}, {
  "type" : "Vector Model",
  "metrics" : [ "request_count", "succ_2xx_count", "error_count", "req_count4xx5xx", "error_rate", "total_token", "avg_total_token", "max_total_token", "p50_total_token", "p80_total_token", "p90_total_token", "p99_total_token", "prompt_token", "completion_token", "avg_prompt_token", "p50_prompt_token", "p80_prompt_token", "p90_prompt_token", "p99_prompt_token", "max_prompt_token", "avg_completion_token", "p50_completion_token", "p80_completion_token", "p90_completion_token", "p99_completion_token", "max_completion_token", "avg_latency", "rpm", "tpm", "avg_ttft", "p50_ttft", "p80_ttft", "p90_ttft", "p99_ttft", "max_ttft", "avg_tpot", "p50_tpot", "p80_tpot", "p90_tpot", "p99_tpot", "max_tpot" ],
  "desc_zh" : "文本向量化",
  "desc_en" : "Vector model"
}, {
  "type" : "Embedding",
  "metrics" : [ "request_count", "succ_2xx_count", "error_count", "req_count4xx5xx", "error_rate", "total_token", "avg_total_token", "max_total_token", "p50_total_token", "p80_total_token", "p90_total_token", "p99_total_token", "prompt_token", "avg_prompt_token", "p50_prompt_token", "p80_prompt_token", "p90_prompt_token", "p99_prompt_token", "max_prompt_token", "avg_latency", "rpm", "tpm" ],
  "desc_zh" : "Embedding模型",
  "desc_en" : "Embedding model"
}, {
  "type" : "Image Understanding",
  "metrics" : [ "request_count", "succ_2xx_count", "error_count", "req_count4xx5xx", "error_rate", "total_token", "avg_total_token", "max_total_token", "p50_total_token", "p80_total_token", "p90_total_token", "p99_total_token", "prompt_token", "completion_token", "avg_prompt_token", "p50_prompt_token", "p80_prompt_token", "p90_prompt_token", "p99_prompt_token", "max_prompt_token", "avg_completion_token", "p50_completion_token", "p80_completion_token", "p90_completion_token", "p99_completion_token", "max_completion_token", "avg_latency", "rpm", "tpm", "avg_ttft", "p50_ttft", "p80_ttft", "p90_ttft", "p99_ttft", "max_ttft", "avg_tpot", "p50_tpot", "p80_tpot", "p90_tpot", "p99_tpot", "max_tpot" ],
  "desc_zh" : "图像理解类模型",
  "desc_en" : "Image understanding model"
}, {
  "type" : "Rerank",
  "metrics" : [ "request_count", "succ_2xx_count", "error_count", "req_count4xx5xx", "error_rate", "total_token", "avg_total_token", "max_total_token", "p50_total_token", "p80_total_token", "p90_total_token", "p99_total_token", "avg_latency", "rpm", "tpm" ],
  "desc_zh" : "重排序类模型",
  "desc_en" : "Rerank model"
} ]

状态码：400

失败响应。

{
  "error_msg" : "The project ID in the request does not match that in the token.",
  "error_code" : "ModelArts.0210"
}

状态码

错误码

请参见错误码。