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* Time granularity and Table of a single model (#4990) * Aiproxy ModelBoard * Add components LineChartComponent and Make some revisions * Time granularity and Table of a single model * Modify the logic and sort the tables in ascending or descending order * Use theme and present in seconds * Add the channel name section (#5005) * Add components LineChartComponent and Make some revisions * Time granularity and Table of a single model * Modify the logic and sort the tables in ascending or descending order * Add the channel name section * The channel_name is transmitted from the outer layer * Restore the channel * perf: dashboard code * perf: ai proxy monitor * code --------- Co-authored-by: Zhuangzai fa <143257420+ctrlz526@users.noreply.github.com>
93 lines
3.6 KiB
JSON
93 lines
3.6 KiB
JSON
{
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"Hunyuan": "腾讯混元",
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"aipoint_usage": "积分消耗",
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"all": "全部",
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"api_key": "API 密钥",
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"avg_response_time": "平均调用时长 (秒)",
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"avg_ttfb": "平均首字时长 (秒)",
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"azure": "微软 Azure",
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"base_url": "代理地址",
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"channel_name": "渠道名",
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"channel_priority": "优先级",
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"channel_priority_tip": "优先级越高的渠道，越容易被请求到",
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"channel_status": "状态",
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"channel_status_auto_disabled": "自动禁用",
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"channel_status_disabled": "禁用",
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"channel_status_enabled": "启用",
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"channel_status_unknown": "未知",
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"channel_type": "厂商",
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"chart_mode_cumulative": "累积",
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"chart_mode_incremental": "分时",
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"clear_model": "清空模型",
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"confirm_delete_channel": "确认删除 【{{name}}】渠道？",
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"copy_model_id_success": "已复制模型id",
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"create_channel": "新增渠道",
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"dashboard_call_trend": "模型调用次数趋势",
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"dashboard_channel": "渠道",
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"dashboard_cost_trend": "积分消耗",
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"dashboard_error_calls": "错误次数",
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"dashboard_input_tokens": "输入Tokens",
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"dashboard_model": "模型",
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"dashboard_no_data": "暂无数据",
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"dashboard_output_tokens": "输出Tokens",
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"dashboard_points": "积分",
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"dashboard_success_calls": "成功次数",
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"dashboard_token_trend": "Tokens使用趋势",
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"dashboard_token_usage": "Tokens 消耗",
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"dashboard_total_calls": "总调用次数:",
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"dashboard_total_cost": "总成本",
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"dashboard_total_cost_label": "总成本:",
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"dashboard_total_tokens": "总Tokens",
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"default_url": "默认地址",
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"detail": "详情",
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"duration": "耗时",
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"edit": "编辑",
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"edit_channel": "渠道配置",
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"enable_channel": "启用",
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"forbid_channel": "禁用",
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"input": "输入",
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"key_type": "API key 格式: ",
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"log": "调用日志",
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"log_detail": "日志详情",
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"log_request_id_search": "根据 requestId 搜索",
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"log_status": "状态",
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"mapping": "模型映射",
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"mapping_tip": "需填写一个有效 Json。可在向实际地址发送请求时，对模型进行映射。例如：\n{\n \"gpt-4o\": \"gpt-4o-test\"\n}\n当 FastGPT 请求 gpt-4o 模型时，会向实际地址发送 gpt-4o-test 的模型，而不是 gpt-4o。",
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"maxToken_tip": "模型 max_tokens 参数",
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"max_rpm": "最大RPM (每分钟请求数)",
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"max_temperature_tip": "模型 temperature 参数，不填则代表模型不支持 temperature 参数。",
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"max_tpm": "最大TPM (每分钟Token数)",
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"model": "模型",
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"model_error_rate": "失败率",
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"model_error_request_times": "失败次数",
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"model_name": "模型名",
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"model_request_times": "请求次数",
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"model_test": "模型测试",
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"model_tokens": "输入/输出 Tokens",
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"monitoring": "监控",
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"output": "输出",
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"request_at": "请求时间",
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"request_duration": "请求时长: {{duration}}s",
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"retry_times": "重试次数",
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"running_test": "测试中",
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"search_model": "搜索模型",
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"select_channel": "选择渠道名",
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"select_model": "选择模型",
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"select_model_placeholder": "选择该渠道下可用的模型",
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"select_provider_placeholder": "搜索厂商",
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"selected_model_empty": "至少选择一个模型",
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"start_test": "批量测试{{num}}个模型",
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"test_failed": "有{{num}}个模型报错",
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"timespan_day": "天",
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"timespan_hour": "小时",
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"timespan_label": "时间颗粒度",
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"timespan_minute": "分钟",
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"total_call_volume": "调用总量",
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"view_chart": "图表",
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"view_table": "表格",
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"vlm_model": "图片理解模型",
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"vlm_model_tip": "用于知识库中对文档中的图片进行额外的索引生成",
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"volunme_of_failed_calls": "调用失败量",
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"waiting_test": "等待测试"
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}
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