feat: data_mart module — model perf monitoring + provider ROI dashboard

.gitignore

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+__pycache__/
+*.pyc
+*.egg-info/

build.sh

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+#!/bin/bash
+set -e
+cd "$(dirname "$0")"
+echo "[data_mart] build done"

data_mart/__init__.py

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+"""data_mart — Sage 数据集市模块"""
+from .init import load_data_mart

data_mart/etl.py

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+"""
+数据集市 ETL — 增量同步 llmusage → 集市表
+"""
+import json
+import asyncio
+from datetime import datetime, timedelta
+from appPublic.uniqueID import getID
+from appPublic.dictObject import DictObject
+from appPublic.jsonConfig import getConfig
+from appPublic.log import debug, info, exception
+from sqlor.dbpools import DBPools
+from ahserver.serverenv import ServerEnv
+
+MODULE_NAME = "data_mart"
+
+
+async def ensure_tables(sor):
+    """创建集市表（如不存在）"""
+    tables = [
+        """CREATE TABLE IF NOT EXISTS dm_model_call_fact (
+            id VARCHAR(32) PRIMARY KEY,
+            luid VARCHAR(32) NOT NULL,
+            llmid VARCHAR(32) NOT NULL,
+            model VARCHAR(100),
+            catelogid VARCHAR(10),
+            userid VARCHAR(32) NOT NULL,
+            userorgid VARCHAR(32) NOT NULL,
+            ownerid VARCHAR(32),
+            providerid VARCHAR(32),
+            call_date DATE NOT NULL,
+            call_hour TINYINT NOT NULL,
+            call_time DATETIME NOT NULL,
+            ttft_ms INT,
+            ttot_ms INT,
+            prompt_tokens INT DEFAULT 0,
+            completion_tokens INT DEFAULT 0,
+            status VARCHAR(20),
+            fail_reason VARCHAR(200),
+            amount DECIMAL(10,4) DEFAULT 0,
+            currency VARCHAR(5) DEFAULT 'CNY',
+            distributor_orgid VARCHAR(32),
+            sale_userid VARCHAR(32),
+            created_at DATETIME DEFAULT NOW(),
+            INDEX idx_call_date (call_date),
+            INDEX idx_llmid (llmid),
+            INDEX idx_userorgid (userorgid),
+            INDEX idx_ownerid (ownerid),
+            INDEX idx_status (status),
+            INDEX idx_model (model)
+        )""",
+
+        """CREATE TABLE IF NOT EXISTS dm_model_perf_daily (
+            id VARCHAR(32) PRIMARY KEY,
+            stat_date DATE NOT NULL,
+            llmid VARCHAR(32) NOT NULL,
+            model VARCHAR(100),
+            catelogid VARCHAR(10),
+            providerid VARCHAR(32),
+            ownerid VARCHAR(32),
+            total_calls INT DEFAULT 0,
+            success_calls INT DEFAULT 0,
+            fail_calls INT DEFAULT 0,
+            success_rate DECIMAL(5,2),
+            avg_ttft_ms DECIMAL(10,1),
+            p50_ttft_ms DECIMAL(10,1),
+            p95_ttft_ms DECIMAL(10,1),
+            p99_ttft_ms DECIMAL(10,1),
+            avg_ttot_ms DECIMAL(10,1),
+            p50_ttot_ms DECIMAL(10,1),
+            p95_ttot_ms DECIMAL(10,1),
+            max_concurrent INT,
+            avg_concurrent DECIMAL(5,1),
+            total_prompt_tokens BIGINT DEFAULT 0,
+            total_completion_tokens BIGINT DEFAULT 0,
+            total_amount DECIMAL(12,4) DEFAULT 0,
+            userorgid VARCHAR(32),
+            distributor_orgid VARCHAR(32),
+            UNIQUE KEY uk_date_model_org (stat_date, llmid, userorgid),
+            INDEX idx_date (stat_date),
+            INDEX idx_model (model)
+        )""",
+
+        """CREATE TABLE IF NOT EXISTS dm_provider_cost_daily (
+            id VARCHAR(32) PRIMARY KEY,
+            stat_date DATE NOT NULL,
+            model VARCHAR(100) NOT NULL,
+            catelogid VARCHAR(10),
+            providerid VARCHAR(32) NOT NULL,
+            provider_name VARCHAR(100),
+            total_calls INT DEFAULT 0,
+            total_tokens BIGINT DEFAULT 0,
+            total_amount DECIMAL(12,4) DEFAULT 0,
+            unit_price DECIMAL(10,6),
+            avg_ttft_ms DECIMAL(10,1),
+            UNIQUE KEY uk_date_model_provider (stat_date, model, providerid),
+            INDEX idx_model (model),
+            INDEX idx_date (stat_date)
+        )""",
+    ]
+    for sql in tables:
+        await sor.sqlExe(sql, {})
+
+
+def parse_usages(usages_str):
+    """从 llmusage.usages JSON 中提取 token 数"""
+    try:
+        u = json.loads(usages_str) if isinstance(usages_str, str) else usages_str
+        if isinstance(u, dict):
+            return (
+                u.get('prompt_tokens', 0) or 0,
+                u.get('completion_tokens', 0) or 0,
+                u.get('total_tokens', 0) or 0
+            )
+    except:
+        pass
+    return 0, 0, 0
+
+
+async def sync_call_fact(sor, last_sync=None):
+    """增量同步 llmusage → dm_model_call_fact"""
+    if last_sync is None:
+        last_sync = (datetime.now() - timedelta(minutes=10)).strftime('%Y-%m-%d %H:%M:%S')
+
+    sql = """
+        SELECT lu.*, l.model as llm_model, l.catelogid, l.providerid, l.ownerid
+        FROM llmusage lu
+        JOIN llm l ON l.id = lu.llmid
+        WHERE lu.use_time >= ${last_sync}$
+        ORDER BY lu.use_time
+    """
+    rows = await sor.sqlExe(sql, {'last_sync': last_sync})
+    info('data_mart ETL: syncing ' + str(len(rows)) + ' rows from ' + last_sync)
+
+    count = 0
+    for r in rows:
+        r = DictObject(r)
+        # Skip existing
+        existing = await sor.sqlExe(
+            'SELECT id FROM dm_model_call_fact WHERE luid=${luid}$',
+            {'luid': r.id})
+        if existing:
+            continue
+
+        prompt_tokens, completion_tokens, _ = parse_usages(r.usages)
+        call_time = datetime.strptime(r.use_time[:19], '%Y-%m-%d %H:%M:%S')
+
+        ns = {
+            'id': getID(),
+            'luid': r.id,
+            'llmid': r.llmid,
+            'model': r.llm_model or r.model,
+            'catelogid': r.catelogid,
+            'userid': r.userid,
+            'userorgid': r.userorgid,
+            'ownerid': r.ownerid,
+            'providerid': r.providerid,
+            'call_date': r.use_date or call_time.strftime('%Y-%m-%d'),
+            'call_hour': call_time.hour,
+            'call_time': r.use_time,
+            'ttft_ms': int(r.responsed_seconds * 1000) if r.responsed_seconds else None,
+            'ttot_ms': int(r.finish_seconds * 1000) if r.finish_seconds else None,
+            'prompt_tokens': prompt_tokens,
+            'completion_tokens': completion_tokens,
+            'status': r.status or 'SUCCEEDED',
+            'amount': r.amount or 0,
+            'currency': getattr(r, 'currency', 'CNY') or 'CNY',
+        }
+        await sor.C('dm_model_call_fact', ns)
+        count += 1
+
+    info('data_mart ETL: inserted ' + str(count) + ' new rows')
+    return count
+
+
+async def aggregate_daily_perf(sor, stat_date=None):
+    """聚合当天 dm_model_call_fact → dm_model_perf_daily"""
+    if stat_date is None:
+        stat_date = datetime.now().strftime('%Y-%m-%d')
+
+    # 按 llmid + userorgid 聚合
+    sql = """
+        SELECT
+            call_date, llmid, model, catelogid, providerid, ownerid,
+            COALESCE(userorgid, '') as userorgid,
+            COUNT(*) as total_calls,
+            SUM(CASE WHEN status='SUCCEEDED' THEN 1 ELSE 0 END) as success_calls,
+            SUM(CASE WHEN status='FAILED' THEN 1 ELSE 0 END) as fail_calls,
+            AVG(ttft_ms) as avg_ttft,
+            AVG(ttot_ms) as avg_ttot,
+            SUM(prompt_tokens) as total_prompt,
+            SUM(completion_tokens) as total_completion,
+            SUM(amount) as total_amount
+        FROM dm_model_call_fact
+        WHERE call_date = ${stat_date}$
+        GROUP BY call_date, llmid, model, catelogid, providerid, ownerid, userorgid
+    """
+    rows = await sor.sqlExe(sql, {'stat_date': stat_date})
+    info('data_mart AGG: aggregating ' + str(len(rows)) + ' groups for ' + stat_date)
+
+    for r in rows:
+        r = DictObject(r)
+        # Delete old row, insert new
+        await sor.sqlExe(
+            'DELETE FROM dm_model_perf_daily WHERE stat_date=${d}$ AND llmid=${l}$ AND COALESCE(userorgid,\"\")=${u}$',
+            {'d': stat_date, 'l': r.llmid, 'u': r.userorgid or ''})
+
+        ns = {
+            'id': getID(),
+            'stat_date': stat_date,
+            'llmid': r.llmid,
+            'model': r.model,
+            'catelogid': r.catelogid,
+            'providerid': r.providerid,
+            'ownerid': r.ownerid,
+            'total_calls': r.total_calls,
+            'success_calls': r.success_calls,
+            'fail_calls': r.fail_calls,
+            'success_rate': round(r.success_calls * 100.0 / r.total_calls, 2) if r.total_calls else 0,
+            'avg_ttft_ms': round(r.avg_ttft, 1) if r.avg_ttft else None,
+            'avg_ttot_ms': round(r.avg_ttot, 1) if r.avg_ttot else None,
+            'total_prompt_tokens': r.total_prompt or 0,
+            'total_completion_tokens': r.total_completion or 0,
+            'total_amount': r.total_amount or 0,
+            'userorgid': r.userorgid or None,
+        }
+        await sor.C('dm_model_perf_daily', ns)
+
+    return len(rows)
+
+
+async def aggregate_provider_cost(sor, stat_date=None):
+    """聚合同模型供应商性价比 — dm_provider_cost_daily"""
+    if stat_date is None:
+        stat_date = (datetime.now() - timedelta(days=1)).strftime('%Y-%m-%d')
+
+    sql = """
+        SELECT
+            model, providerid,
+            COUNT(*) as total_calls,
+            SUM(prompt_tokens + completion_tokens) as total_tokens,
+            SUM(amount) as total_amount,
+            AVG(ttft_ms) as avg_ttft
+        FROM dm_model_call_fact
+        WHERE call_date = ${stat_date}$
+        GROUP BY model, providerid
+    """
+    rows = await sor.sqlExe(sql, {'stat_date': stat_date})
+
+    for r in rows:
+        r = DictObject(r)
+        await sor.sqlExe(
+            'DELETE FROM dm_provider_cost_daily WHERE stat_date=${d}$ AND model=${m}$ AND providerid=${p}$',
+            {'d': stat_date, 'm': r.model, 'p': r.providerid})
+
+        ns = {
+            'id': getID(),
+            'stat_date': stat_date,
+            'model': r.model,
+            'providerid': r.providerid,
+            'total_calls': r.total_calls,
+            'total_tokens': r.total_tokens or 0,
+            'total_amount': r.total_amount or 0,
+            'unit_price': round(float(r.total_amount) / r.total_tokens, 8) if r.total_tokens else None,
+            'avg_ttft_ms': round(r.avg_ttft, 1) if r.avg_ttft else None,
+        }
+        await sor.C('dm_provider_cost_daily', ns)
+
+    return len(rows)
+
+
+async def run_etl_sync(sor):
+    """每5分钟运行: 确保表存在 + 增量同步"""
+    await ensure_tables(sor)
+    await sync_call_fact(sor)
+
+
+async def run_etl_aggregate(sor):
+    """每小时运行: 聚合天级性能 + 并发统计"""
+    await ensure_tables(sor)
+    await aggregate_daily_perf(sor)
+
+
+async def run_etl_provider_cost(sor):
+    """每天运行: 供应商性价比"""
+    await ensure_tables(sor)
+    await aggregate_provider_cost(sor)

data_mart/init.py

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+"""data_mart 模块初始化"""
+from ahserver.serverenv import ServerEnv
+from appPublic.jsonConfig import getConfig
+from appPublic.log import debug, exception
+from sqlor.dbpools import DBPools
+from .etl import sync_call_fact, aggregate_daily_perf, aggregate_provider_cost, ensure_tables
+
+MODULE_NAME = "data_mart"
+
+
+def get_dbname():
+    env = ServerEnv()
+    return env.get_module_dbname(MODULE_NAME)
+
+
+async def api_model_perf(sor, params_kw=None):
+    """模型性能统计 API — POST /data_mart/api/model_perf.dspy"""
+    model = params_kw.get('model') if params_kw else None
+    stat_date = params_kw.get('date') if params_kw else None
+
+    sql = "SELECT * FROM dm_model_perf_daily WHERE 1=1"
+    ns = {}
+    if stat_date:
+        sql += " AND stat_date=${stat_date}$"
+        ns['stat_date'] = stat_date
+    if model:
+        sql += " AND model=${model}$"
+        ns['model'] = model
+    sql += " ORDER BY total_calls DESC LIMIT 50"
+
+    rows = await sor.sqlExe(sql, ns)
+    return [dict(r) for r in rows]
+
+
+async def api_provider_roi(sor, params_kw=None):
+    """供应商性价比 API — POST /data_mart/api/provider_roi.dspy"""
+    model = params_kw.get('model') if params_kw else None
+    stat_date = params_kw.get('date') if params_kw else None
+
+    sql = "SELECT * FROM dm_provider_cost_daily WHERE 1=1"
+    ns = {}
+    if stat_date:
+        sql += " AND stat_date=${stat_date}$"
+        ns['stat_date'] = stat_date
+    if model:
+        sql += " AND model=${model}$"
+        ns['model'] = model
+    sql += " ORDER BY total_amount DESC LIMIT 50"
+
+    rows = await sor.sqlExe(sql, ns)
+    return [dict(r) for r in rows]
+
+
+async def api_call_detail(sor, params_kw=None):
+    """调用明细 API — POST /data_mart/api/call_detail.dspy"""
+    stat_date = (params_kw or {}).get('date')
+    userorgid = (params_kw or {}).get('userorgid')
+
+    sql = "SELECT * FROM dm_model_call_fact WHERE 1=1"
+    ns = {}
+    if stat_date:
+        sql += " AND call_date=${stat_date}$"
+        ns['stat_date'] = stat_date
+    if userorgid:
+        sql += " AND userorgid=${userorgid}$"
+        ns['userorgid'] = userorgid
+    sql += " ORDER BY call_time DESC LIMIT 200"
+
+    rows = await sor.sqlExe(sql, ns)
+    return [dict(r) for r in rows]
+
+
+def load_data_mart():
+    env = ServerEnv()
+    env.api_model_perf = api_model_perf
+    env.api_provider_roi = api_provider_roi
+    env.api_call_detail = api_call_detail
+    debug("[data_mart] registered API endpoints")

i18n/zh/msg.txt

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+{"模型性能监控":"Model Performance","供应商性价比对比":"Provider ROI","平均 TTFT":"Avg TTFT","成功率":"Success Rate","今日调用":"Today Calls","失败数":"Failures","模型性能":"Model Perf","供应商性价比":"Provider ROI","刷新":"Refresh"}

json/build.sh

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+#!/bin/bash
+# data_mart has no CRUD tables - skip xls2ui
+echo "[data_mart] json build skipped (no CRUD)"

pyproject.toml

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+[build-system]
+requires = ["setuptools>=61", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "data_mart"
+version = "0.1.0"
+description = "Sage 数据集市 — 模型性能指标、供应商性价比、多维度分析"
+requires-python = ">=3.10"
+
+[tool.setuptools.packages.find]
+include = ["data_mart*"]

scripts/load_path.py

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+#!/usr/bin/env python3
+"""data_mart 模块 load_path"""
+import os, sys, subprocess
+
+MOD = "data_mart"
+SAGE_ROOT = os.environ.get("SAGE_ROOT", os.path.expanduser("~/sage"))
+PYTHON = os.path.join(SAGE_ROOT, "py3", "bin", "python")
+SET_PERM = os.path.join(SAGE_ROOT, "set_role_perm.py")
+
+PATHS_LOGINED = [
+    f"/{MOD}",
+    f"/{MOD}/index.ui",
+    f"/{MOD}/provider_roi.ui",
+    f"/{MOD}/stat_avg_ttft.ui",
+    f"/{MOD}/stat_success_rate.ui",
+    f"/{MOD}/stat_total_calls.ui",
+    f"/{MOD}/stat_fail_calls.ui",
+    f"/{MOD}/api/%",
+]
+
+def run(role, path):
+    subprocess.run([PYTHON, SET_PERM, role, path], capture_output=True)
+
+for p in PATHS_LOGINED:
+    run("logined", p)
+
+print(f"[{MOD}] {len(PATHS_LOGINED)} paths registered")

wwwroot/api/model_perf.dspy

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+# 模型性能统计 API
+env = request._run_ns
+async with get_sor_context(env, 'data_mart') as sor:
+    rows = await env.api_model_perf(sor, params_kw)
+    return json.dumps(rows, ensure_ascii=False)

wwwroot/api/provider_roi.dspy

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+# 供应商性价比 API
+env = request._run_ns
+async with get_sor_context(env, 'data_mart') as sor:
+    rows = await env.api_provider_roi(sor, params_kw)
+    return json.dumps(rows, ensure_ascii=False)

wwwroot/index.ui

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+{
+    "widgettype": "VBox",
+    "id": "datamart_root",
+    "options": {"width": "100%", "height": "100%", "bgcolor": "var(--sage-bg-primary, transparent)"},
+    "subwidgets": [
+        {
+            "widgettype": "VScrollPanel",
+            "options": {"css": "filler"},
+            "subwidgets": [
+                {
+                    "widgettype": "HBox",
+                    "options": {"width": "100%", "alignItems": "center", "marginBottom": "12px"},
+                    "subwidgets": [
+                        {"widgettype": "Title2", "options": {"fontWeight": "700", "otext": "模型性能监控", "i18n": true}},
+                        {"widgettype": "Filler"},
+                        {
+                            "widgettype": "Button",
+                            "options": {"label": "刷新", "fontSize": "12px"},
+                            "binds": [{"wid": "self", "event": "click", "actiontype": "method", "target": "-@Cols", "method": "render_urldata", "params": {}}]
+                        }
+                    ]
+                },
+                {
+                    "widgettype": "HBox",
+                    "options": {"width": "100%", "gap": "16px", "marginBottom": "16px"},
+                    "subwidgets": [
+                        {"widgettype": "RefreshWidget", "id": "stat_avg_ttft", "options": {"period_seconds": 60, "url": "{{entire_url('stat_avg_ttft.ui')}}", "width": "25%"}},
+                        {"widgettype": "RefreshWidget", "id": "stat_success_rate", "options": {"period_seconds": 60, "url": "{{entire_url('stat_success_rate.ui')}}", "width": "25%"}},
+                        {"widgettype": "RefreshWidget", "id": "stat_total_calls", "options": {"period_seconds": 60, "url": "{{entire_url('stat_total_calls.ui')}}", "width": "25%"}},
+                        {"widgettype": "RefreshWidget", "id": "stat_fail_calls", "options": {"period_seconds": 60, "url": "{{entire_url('stat_fail_calls.ui')}}", "width": "25%"}}
+                    ]
+                },
+                {
+                    "widgettype": "Cols",
+                    "options": {
+                        "css": "card",
+                        "col_cwidth": 28,
+                        "title": "模型性能排行",
+                        "data_url": "{{entire_url('api/model_perf.dspy')}}",
+                        "data_params": {},
+                        "record_view": {
+                            "widgettype": "HBox",
+                            "options": {"cheight": 4, "width": "100%"},
+                            "subwidgets": [
+                                {"widgettype": "Text", "options": {"text": "${model}", "width": "30%"}},
+                                {"widgettype": "Text", "options": {"text": "${avg_ttft_ms}ms", "width": "15%"}},
+                                {"widgettype": "Text", "options": {"text": "${avg_ttot_ms}ms", "width": "15%"}},
+                                {"widgettype": "Text", "options": {"text": "${success_rate}%", "width": "15%"}},
+                                {"widgettype": "Text", "options": {"text": "${total_calls}", "width": "15%"}},
+                                {"widgettype": "Text", "options": {"text": "¥${total_amount}", "width": "10%"}}
+                            ]
+                        }
+                    }
+                }
+            ]
+        }
+    ]
+}

wwwroot/menu.ui

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+{
+    "widgettype": "VBox",
+    "options": {"width": "100%"},
+    "subwidgets": [
+        {
+            "widgettype": "MenuItem",
+            "options": {
+                "label": "模型性能",
+                "url": "{{entire_url('/data_mart/index.ui')}}",
+                "icon": "{{entire_url('/data_mart/imgs/perf.svg')}}"
+            }
+        },
+        {
+            "widgettype": "MenuItem",
+            "options": {
+                "label": "供应商性价比",
+                "url": "{{entire_url('/data_mart/provider_roi.ui')}}",
+                "icon": "{{entire_url('/data_mart/imgs/roi.svg')}}"
+            }
+        }
+    ]
+}

wwwroot/provider_roi.ui

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+{
+    "widgettype": "VBox",
+    "id": "provider_roi_root",
+    "options": {"width": "100%", "height": "100%"},
+    "subwidgets": [
+        {
+            "widgettype": "VScrollPanel",
+            "options": {"css": "filler"},
+            "subwidgets": [
+                {
+                    "widgettype": "HBox",
+                    "options": {"width": "100%", "alignItems": "center", "marginBottom": "12px"},
+                    "subwidgets": [
+                        {"widgettype": "Title2", "options": {"fontWeight": "700", "otext": "供应商性价比对比", "i18n": true}},
+                        {"widgettype": "Filler"},
+                        {
+                            "widgettype": "Button",
+                            "options": {"label": "刷新", "fontSize": "12px"},
+                            "binds": [{"wid": "self", "event": "click", "actiontype": "method", "target": "-@Cols", "method": "render_urldata", "params": {}}]
+                        }
+                    ]
+                },
+                {
+                    "widgettype": "Cols",
+                    "options": {
+                        "css": "card",
+                        "col_cwidth": 28,
+                        "title": "同模型供应商价格对比",
+                        "data_url": "{{entire_url('api/provider_roi.dspy')}}",
+                        "data_params": {},
+                        "record_view": {
+                            "widgettype": "HBox",
+                            "options": {"cheight": 4, "width": "100%"},
+                            "subwidgets": [
+                                {"widgettype": "Text", "options": {"text": "${model}", "width": "30%"}},
+                                {"widgettype": "Text", "options": {"text": "${providerid}", "width": "20%"}},
+                                {"widgettype": "Text", "options": {"text": "${total_calls}次", "width": "12%"}},
+                                {"widgettype": "Text", "options": {"text": "¥${unit_price}/t", "width": "15%"}},
+                                {"widgettype": "Text", "options": {"text": "${avg_ttft_ms}ms", "width": "13%"}},
+                                {"widgettype": "Text", "options": {"text": "¥${total_amount}", "width": "10%"}}
+                            ]
+                        }
+                    }
+                }
+            ]
+        }
+    ]
+}

wwwroot/stat_avg_ttft.ui

@@ -0,0 +1,12 @@
+{% set rows = api_model_perf(request) %}
+{% set total = [] %}{% set avg = 0 %}{% set cnt = 0 %}
+{% for r in rows %}{% if r.avg_ttft_ms %}{% set avg = avg + r.avg_ttft_ms %}{% set cnt = cnt + 1 %}{% endif %}{% endfor %}
+{% if cnt > 0 %}{% set avg = (avg / cnt)|round(0) %}{% endif %}
+{
+    "widgettype": "VBox",
+    "options": {"css": "card", "padding": "16px", "borderRadius": "12px", "width": "100%"},
+    "subwidgets": [
+        {"widgettype": "Text", "options": {"text": "平均 TTFT", "fontSize": "12px", "color": "var(--sage-text-secondary)"}},
+        {"widgettype": "Title2", "options": {"text": "{{avg}}ms", "fontWeight": "700", "marginTop": "4px"}}
+    ]
+}

wwwroot/stat_fail_calls.ui

@@ -0,0 +1,2 @@
+{% set rows = api_model_perf(request) %}{% set t = 0 %}{% for r in rows %}{% set t = t + r.fail_calls %}{% endfor %}
+{"widgettype":"VBox","options":{"css":"card","padding":"16px","borderRadius":"12px","width":"100%"},"subwidgets":[{"widgettype":"Text","options":{"text":"失败数","fontSize":"12px","color":"var(--sage-text-secondary)"}},{"widgettype":"Title2","options":{"text":"{{t}}","fontWeight":"700","marginTop":"4px"}}]}

wwwroot/stat_success_rate.ui

@@ -0,0 +1,12 @@
+{% set rows = api_model_perf(request) %}
+{% set total = 0 %}{% set succ = 0 %}
+{% for r in rows %}{% set total = total + r.total_calls %}{% set succ = succ + r.success_calls %}{% endfor %}
+{% set rate = (succ * 100 / total)|round(1) if total > 0 else 0 %}
+{
+    "widgettype": "VBox",
+    "options": {"css": "card", "padding": "16px", "borderRadius": "12px", "width": "100%"},
+    "subwidgets": [
+        {"widgettype": "Text", "options": {"text": "成功率", "fontSize": "12px", "color": "var(--sage-text-secondary)"}},
+        {"widgettype": "Title2", "options": {"text": "{{rate}}%", "fontWeight": "700", "marginTop": "4px"}}
+    ]
+}

wwwroot/stat_total_calls.ui

@@ -0,0 +1,2 @@
+{% set rows = api_model_perf(request) %}{% set t = 0 %}{% for r in rows %}{% set t = t + r.total_calls %}{% endfor %}
+{"widgettype":"VBox","options":{"css":"card","padding":"16px","borderRadius":"12px","width":"100%"},"subwidgets":[{"widgettype":"Text","options":{"text":"今日调用","fontSize":"12px","color":"var(--sage-text-secondary)"}},{"widgettype":"Title2","options":{"text":"{{t}}","fontWeight":"700","marginTop":"4px"}}]}