690602:1334 ADR-033-233 #03
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This commit is contained in:
2026-06-02 13:34:22 +07:00
parent b939a25456
commit cb9ecb2de6
5 changed files with 498 additions and 82 deletions
+70 -13
View File
@@ -24,7 +24,12 @@ import { Textarea } from '@/components/ui/textarea';
import { Progress } from '@/components/ui/progress';
import { useAiStatus, useToggleAiFeatures, useAiHealth } from '@/hooks/use-ai-status';
import { projectService } from '@/lib/services/project.service';
import { adminAiService, AiSandboxJobResult, AiAvailableModel } from '@/lib/services/admin-ai.service';
import {
adminAiService,
AiSandboxJobResult,
AiAvailableModel,
AiRagCitation,
} from '@/lib/services/admin-ai.service';
import { toast } from 'sonner';
import OcrSandboxPromptManager from '@/components/admin/ai/OcrSandboxPromptManager';
import OcrEngineSelector from '@/components/admin/ai/OcrEngineSelector';
@@ -35,6 +40,48 @@ interface SandboxProject {
projectCode: string;
}
interface VramLoadedModelView {
modelId: string;
modelName: string;
vramUsageMB?: number;
}
function ensureArray<T>(value: unknown): T[] {
return Array.isArray(value) ? value : [];
}
function normalizeLoadedModels(value: unknown): VramLoadedModelView[] {
if (!Array.isArray(value)) {
return [];
}
return value.map((item, index) => {
if (typeof item === 'string') {
return {
modelId: `${item}-${index}`,
modelName: item,
};
}
if (item && typeof item === 'object') {
const model = item as {
modelId?: string;
modelName?: string;
name?: string;
vramUsageMB?: number;
};
const modelName = model.modelName ?? model.name ?? `model-${index + 1}`;
return {
modelId: model.modelId ?? modelName,
modelName,
vramUsageMB: model.vramUsageMB,
};
}
return {
modelId: `unknown-${index}`,
modelName: `Unknown Model ${index + 1}`,
};
});
}
export default function AiAdminConsolePage() {
const { data, isLoading, isError, refetch, isFetching } = useAiStatus();
const { data: health, isLoading: isHealthLoading, refetch: refetchHealth } = useAiHealth();
@@ -56,7 +103,7 @@ export default function AiAdminConsolePage() {
return await adminAiService.getAvailableModels();
},
});
const availableModels = aiModelsData?.models ?? [];
const availableModels = ensureArray<AiAvailableModel>(aiModelsData?.models);
const activeModel = aiModelsData?.activeModel ?? '';
// VRAM Monitoring State (T034, T036, US2)
@@ -75,6 +122,13 @@ export default function AiAdminConsolePage() {
return res as SandboxProject[];
},
});
const healthOllamaModels = ensureArray<string>(health?.ollama?.models);
const healthQdrantCollections = ensureArray<string>(health?.qdrant?.collections);
const vramLoadedModels = normalizeLoadedModels(vramStatus?.loadedModels);
const sandboxProjects = ensureArray<SandboxProject>(projects);
const sandboxCitations = ensureArray<AiRagCitation>(
sandboxJobResult?.citations
);
const handleToggle = async (enabled: boolean): Promise<void> => {
await toggleMutation.mutateAsync(enabled);
@@ -242,8 +296,8 @@ export default function AiAdminConsolePage() {
<div className="space-y-1">
<span className="text-xs text-muted-foreground">:</span>
<div className="flex flex-wrap gap-1">
{health?.ollama?.models && health.ollama.models.length > 0 ? (
health.ollama.models.map((m) => (
{healthOllamaModels.length > 0 ? (
healthOllamaModels.map((m) => (
<Badge key={m} variant="secondary" className="text-[10px] py-0 px-1">
{m}
</Badge>
@@ -274,8 +328,8 @@ export default function AiAdminConsolePage() {
<div className="space-y-1">
<span className="text-xs text-muted-foreground">:</span>
<div className="flex flex-wrap gap-1">
{health?.qdrant?.collections && health.qdrant.collections.length > 0 ? (
health.qdrant.collections.map((c) => (
{healthQdrantCollections.length > 0 ? (
healthQdrantCollections.map((c) => (
<Badge key={c} variant="outline" className="text-[10px] py-0 px-1 bg-background/30">
{c}
</Badge>
@@ -394,10 +448,13 @@ export default function AiAdminConsolePage() {
<div className="space-y-1 text-xs">
<span className="text-muted-foreground block"> GPU :</span>
<div className="flex flex-wrap gap-1 mt-1">
{vramStatus.loadedModels && vramStatus.loadedModels.length > 0 ? (
vramStatus.loadedModels.map((m) => (
<Badge key={m.modelId || m.modelName} className="bg-primary/10 text-primary border-none hover:bg-primary/20 text-[10px]">
{m.modelName} ({m.vramUsageMB} MB)
{vramLoadedModels.length > 0 ? (
vramLoadedModels.map((m) => (
<Badge key={m.modelId} className="bg-primary/10 text-primary border-none hover:bg-primary/20 text-[10px]">
{m.modelName}
{typeof m.vramUsageMB === 'number'
? ` (${m.vramUsageMB} MB)`
: ''}
</Badge>
))
) : (
@@ -627,7 +684,7 @@ export default function AiAdminConsolePage() {
<SelectValue placeholder="-- กรุณาเลือกโครงการ --" />
</SelectTrigger>
<SelectContent>
{projects.map((proj) => (
{sandboxProjects.map((proj) => (
<SelectItem key={proj.publicId} value={proj.publicId}>
{proj.projectName} ({proj.projectCode})
</SelectItem>
@@ -728,9 +785,9 @@ export default function AiAdminConsolePage() {
</CardTitle>
</CardHeader>
<CardContent>
{sandboxJobResult.citations && sandboxJobResult.citations.length > 0 ? (
{sandboxCitations.length > 0 ? (
<div className="grid gap-3 sm:grid-cols-1">
{sandboxJobResult.citations.map((cite, index) => (
{sandboxCitations.map((cite, index) => (
<div
key={cite.pointId || index}
className="rounded-lg border border-border/40 bg-background/30 p-3 hover:bg-background/60 transition-colors space-y-2"
+55 -2
View File
@@ -9,6 +9,8 @@
// - 2026-05-29: เพิ่ม ocrText, ocrUsed, promptVersionUsed ใน AiSandboxJobResult
// - 2026-05-30: เพิ่มเมธอด getOcrEngines และ selectOcrEngine สำหรับจัดการ OCR engines (T017, T018, US1)
// - 2026-05-30: เพิ่ม getVramStatus และปรับปรุง getAvailableModels/setActiveModel/addModel ให้เรียกใช้ endpoints ใหม่ที่มี VRAM capacity check (T031-T034, US2)
// - 2026-06-02: แก้ endpoint getAvailableModels ให้ตรงกับ backend admin route (/ai/admin/models)
// - 2026-06-02: normalize VRAM response ให้รองรับ field names จาก backend ปัจจุบันและรูปแบบ loadedModels แบบเดิม
import api from '../api/client';
@@ -91,6 +93,20 @@ export interface VramStatusResponse {
lastUpdated: string;
}
interface RawVramStatusResponse {
totalVRAMMB?: number;
usedVRAMMB?: number;
usagePercent?: number;
thresholdPercent?: number;
loadedModels?: Array<string | LoadedModelInfo>;
canLoadModel?: boolean;
lastUpdated?: string;
totalVramMb?: number;
usedVramMb?: number;
freeVramMb?: number;
hasCapacity?: boolean;
}
export interface AiAvailableModel {
id?: number;
modelId?: string;
@@ -121,6 +137,43 @@ const extractData = <T>(value: unknown): T => {
return value as T;
};
const normalizeLoadedModels = (
models: Array<string | LoadedModelInfo> | undefined
): LoadedModelInfo[] => {
if (!Array.isArray(models)) {
return [];
}
return models.map((model, index) => {
if (typeof model === 'string') {
return {
modelId: `${model}-${index}`,
modelName: model,
vramUsageMB: 0,
};
}
return model;
});
};
const normalizeVramStatus = (value: unknown): VramStatusResponse => {
const raw = extractData<RawVramStatusResponse>(value);
const totalVRAMMB = raw.totalVRAMMB ?? raw.totalVramMb ?? 0;
const usedVRAMMB = raw.usedVRAMMB ?? raw.usedVramMb ?? 0;
const usagePercent =
raw.usagePercent ??
(totalVRAMMB > 0 ? Math.round((usedVRAMMB / totalVRAMMB) * 100) : 0);
return {
totalVRAMMB,
usedVRAMMB,
usagePercent,
thresholdPercent: raw.thresholdPercent ?? 90,
loadedModels: normalizeLoadedModels(raw.loadedModels),
canLoadModel: raw.canLoadModel ?? raw.hasCapacity ?? false,
lastUpdated: raw.lastUpdated ?? new Date().toISOString(),
};
};
/** Service สำหรับเรียก AI Admin Console API ผ่าน DMS Backend เท่านั้น */
export const adminAiService = {
getStatus: async (): Promise<AiAdminSettings> => {
@@ -199,7 +252,7 @@ export const adminAiService = {
// --- AI Model Management (ADR-027, US2) ---
getAvailableModels: async (): Promise<AiModelsResponse> => {
const { data } = await api.get('/ai/models');
const { data } = await api.get('/ai/admin/models');
return extractData<AiModelsResponse>(data);
},
@@ -215,7 +268,7 @@ export const adminAiService = {
getVramStatus: async (): Promise<VramStatusResponse> => {
const { data } = await api.get('/ai/vram/status');
return extractData<VramStatusResponse>(data);
return normalizeVramStatus(data);
},
addModel: async (
@@ -0,0 +1,240 @@
# File: /volume1/np-dms/monitoring/docker-compose.yml
# DMS Container v1.8.6: Application name: lcbp3-monitoring
# Deploy on: ASUSTOR AS5403T
# Services: prometheus, grafana, node-exporter, cadvisor, uptime-kuma, loki, promtail
x-restart: &restart_policy
restart: unless-stopped
x-logging: &default_logging
logging:
driver: "json-file"
options:
max-size: "10m"
max-file: "5"
name: lcbp3-monitoring
networks:
lcbp3:
external: true
services:
# ----------------------------------------------------------------
# 1. Prometheus (Metrics Collection & Storage)
# ----------------------------------------------------------------
prometheus:
<<: [*restart_policy, *default_logging]
image: prom/prometheus:v2.48.0
container_name: prometheus
deploy:
resources:
limits:
cpus: "1.0"
memory: 1G
reservations:
cpus: "0.25"
memory: 256M
environment:
TZ: "Asia/Bangkok"
command:
- "--config.file=/etc/prometheus/prometheus.yml"
- "--storage.tsdb.path=/prometheus"
- "--storage.tsdb.retention.time=30d"
- "--web.enable-lifecycle"
ports:
- "9090:9090"
networks:
- lcbp3
volumes:
- "/volume1/np-dms/monitoring/prometheus/config:/etc/prometheus:ro"
- "/volume1/np-dms/monitoring/prometheus/data:/prometheus"
healthcheck:
test: ["CMD", "wget", "--spider", "-q", "http://localhost:9090/-/healthy"]
interval: 30s
timeout: 10s
retries: 3
# ----------------------------------------------------------------
# 2. Grafana (Dashboard & Visualization)
# ----------------------------------------------------------------
grafana:
<<: [*restart_policy, *default_logging]
image: grafana/grafana:10.2.2
container_name: grafana
deploy:
resources:
limits:
cpus: "1.0"
memory: 512M
reservations:
cpus: "0.25"
memory: 128M
env_file:
- .env
environment:
TZ: "Asia/Bangkok"
GF_SECURITY_ADMIN_USER: admin
GF_SECURITY_ADMIN_PASSWORD: ${GRAFANA_ADMIN_PASSWORD:?GRAFANA_ADMIN_PASSWORD required}
GF_SERVER_ROOT_URL: "https://grafana.np-dms.work"
GF_INSTALL_PLUGINS: grafana-clock-panel,grafana-piechart-panel
ports:
- "3003:3000"
networks:
- lcbp3
volumes:
- "/volume1/np-dms/monitoring/grafana/data:/var/lib/grafana"
depends_on:
- prometheus
healthcheck:
test:
[
"CMD-SHELL",
"wget --spider -q http://localhost:3000/api/health || exit 1",
]
interval: 30s
timeout: 10s
retries: 3
# ----------------------------------------------------------------
# 3. Uptime Kuma (Service Availability Monitoring)
# ----------------------------------------------------------------
uptime-kuma:
<<: [*restart_policy, *default_logging]
image: louislam/uptime-kuma:1
container_name: uptime-kuma
deploy:
resources:
limits:
cpus: "0.5"
memory: 256M
environment:
TZ: "Asia/Bangkok"
ports:
- "3001:3001"
networks:
- lcbp3
volumes:
- "/volume1/np-dms/monitoring/uptime-kuma/data:/app/data"
healthcheck:
test:
["CMD-SHELL", "curl -f http://localhost:3001/api/entry-page || exit 1"]
interval: 30s
timeout: 10s
retries: 3
# ----------------------------------------------------------------
# 4. Node Exporter (Host Metrics - ASUSTOR)
# ----------------------------------------------------------------
node-exporter:
<<: [*restart_policy, *default_logging]
image: prom/node-exporter:v1.7.0
container_name: node-exporter
deploy:
resources:
limits:
cpus: "0.5"
memory: 128M
environment:
TZ: "Asia/Bangkok"
command:
- "--path.procfs=/host/proc"
- "--path.sysfs=/host/sys"
- "--collector.filesystem.mount-points-exclude=^/(sys|proc|dev|host|etc)($$|/)"
ports:
- "9100:9100"
networks:
- lcbp3
volumes:
- /proc:/host/proc:ro
- /sys:/host/sys:ro
- /:/rootfs:ro
healthcheck:
test: ["CMD", "wget", "--spider", "-q", "http://localhost:9100/metrics"]
interval: 30s
timeout: 10s
retries: 3
# ----------------------------------------------------------------
# 5. cAdvisor (Container Metrics - ASUSTOR)
# ----------------------------------------------------------------
cadvisor:
<<: [*restart_policy, *default_logging]
image: gcr.io/cadvisor/cadvisor:v0.47.2
container_name: cadvisor
deploy:
resources:
limits:
cpus: "0.5"
memory: 256M
environment:
TZ: "Asia/Bangkok"
# H4: cAdvisor binds 8080 container map 8088 host
ports:
- "8088:8080"
networks:
- lcbp3
volumes:
- /:/rootfs:ro
- /var/run:/var/run:ro
- /sys:/sys:ro
- /var/lib/docker/:/var/lib/docker:ro
healthcheck:
test: ["CMD", "wget", "--spider", "-q", "http://localhost:8080/healthz"]
interval: 30s
timeout: 10s
retries: 3
# ----------------------------------------------------------------
# 6. Loki (Log Aggregation)
# ----------------------------------------------------------------
loki:
<<: [*restart_policy, *default_logging]
image: grafana/loki:2.9.0
container_name: loki
deploy:
resources:
limits:
cpus: "0.5"
memory: 512M
environment:
TZ: "Asia/Bangkok"
command: -config.file=/etc/loki/local-config.yaml
ports:
- "3100:3100"
networks:
- lcbp3
volumes:
- "/volume1/np-dms/monitoring/loki/data:/loki"
healthcheck:
test: ["CMD", "wget", "--spider", "-q", "http://localhost:3100/ready"]
interval: 30s
timeout: 10s
retries: 3
# ----------------------------------------------------------------
# 7. Promtail (Log Shipper)
# ----------------------------------------------------------------
promtail:
<<: [*restart_policy, *default_logging]
image: grafana/promtail:2.9.0
container_name: promtail
# L5: root /var/lib/docker/containers
# mount read-only
user: "0:0"
deploy:
resources:
limits:
cpus: "0.5"
memory: 256M
environment:
TZ: "Asia/Bangkok"
command: -config.file=/etc/promtail/promtail-config.yml
networks:
- lcbp3
volumes:
- "/volume1/np-dms/monitoring/promtail/config:/etc/promtail:ro"
- "/var/run/docker.sock:/var/run/docker.sock:ro"
- "/var/lib/docker/containers:/var/lib/docker/containers:ro"
depends_on:
- loki
@@ -0,0 +1,60 @@
global:
scrape_interval: 15s
evaluation_interval: 15s
scrape_configs:
# Prometheus self-monitoring (ASUSTOR)
- job_name: "prometheus"
static_configs:
- targets: ["localhost:9090"]
# ============================================
# ASUSTOR Metrics (Local)
# ============================================
# Host metrics from Node Exporter (ASUSTOR)
- job_name: "asustor-node"
static_configs:
- targets: ["node-exporter:9100"]
labels:
host: "asustor"
# Container metrics from cAdvisor (ASUSTOR)
- job_name: "asustor-cadvisor"
static_configs:
- targets: ["cadvisor:8080"]
labels:
host: "asustor"
# ============================================
# QNAP Metrics (Remote - 192.168.10.8)
# ============================================
# Host metrics from Node Exporter (QNAP)
- job_name: "qnap-node"
static_configs:
- targets: ["192.168.10.8:9100"]
labels:
host: "qnap"
# Container metrics from cAdvisor (QNAP)
- job_name: "qnap-cadvisor"
static_configs:
- targets: ["192.168.10.8:8088"]
labels:
host: "qnap"
# Backend NestJS application (QNAP)
- job_name: "backend"
static_configs:
- targets: ["192.168.10.8:3000"]
labels:
host: "qnap"
metrics_path: "/metrics"
# MariaDB Exporter (optional - QNAP)
- job_name: "mariadb"
static_configs:
- targets: ["192.168.10.8:9104"]
labels:
host: "qnap"
@@ -1,92 +1,98 @@
# File: specs/04-Infrastructure-OPS/04-00-docker-compose/ASUSTOR/monitoring/prometheus/config/prometheus.yml
# Prometheus Configuration — รัน บน ASUSTOR AS5403T (lcbp3-monitoring stack)
# Change Log:
# - 2026-06-02: Initial config — scrape jobs สำหรับ ASUSTOR local + Desk-5439 remote
# - 2026-06-02: Initial config — merge จาก 0.yml (existing) + เพิ่ม ollama-metrics job
#
# Deploy path: /volume1/np-dms/monitoring/prometheus/config/prometheus.yml
# Mount (read-only): docker-compose volume → /etc/prometheus/prometheus.yml
#
# NOTE: ไฟล์นี้รวม 0.yml (config เดิมบน ASUSTOR) + job ollama-metrics ใหม่
# เมื่อ deploy แล้วให้ลบ 0.yml ออก หรือ rename เป็น 0.yml.bak
global:
scrape_interval: 15s # ดึง metrics ทุก 15 วินาที (default)
evaluation_interval: 15s # ประเมิน rules ทุก 15 วินาที
scrape_timeout: 10s
# Labels ที่ติดไปกับทุก time series ที่ scrape ได้
external_labels:
environment: 'production'
cluster: 'lcbp3'
# ─── Alerting (optional — เชื่อม Alertmanager เมื่อต้องการ) ──────────────────
# alerting:
# alertmanagers:
# - static_configs:
# - targets: ['alertmanager:9093']
# ─── Rules (optional) ────────────────────────────────────────────────────────
# rule_files:
# - /etc/prometheus/rules/*.yml
scrape_interval: 15s
evaluation_interval: 15s
# ─── Scrape Jobs ─────────────────────────────────────────────────────────────
scrape_configs:
# ----------------------------------------------------------------
# 1. Prometheus self-monitoring (ASUSTOR)
# ----------------------------------------------------------------
- job_name: 'prometheus'
- job_name: "prometheus"
static_configs:
- targets: ['localhost:9090']
labels:
host: 'asustor'
service: 'prometheus'
- targets: ["localhost:9090"]
# ----------------------------------------------------------------
# 2. Node Exporter — Host metrics ของ ASUSTOR
# ----------------------------------------------------------------
- job_name: 'node-exporter-asustor'
# ============================================
# ASUSTOR Metrics (Local)
# ============================================
# Host metrics from Node Exporter (ASUSTOR)
- job_name: "asustor-node"
static_configs:
- targets: ['node-exporter:9100']
- targets: ["node-exporter:9100"]
labels:
host: 'asustor'
service: 'node-exporter'
host: "asustor"
# ----------------------------------------------------------------
# 3. cAdvisor — Container metrics ของ ASUSTOR
# ----------------------------------------------------------------
- job_name: 'cadvisor-asustor'
# Container metrics from cAdvisor (ASUSTOR)
- job_name: "asustor-cadvisor"
static_configs:
- targets: ['cadvisor:8080']
- targets: ["cadvisor:8080"]
labels:
host: 'asustor'
service: 'cadvisor'
host: "asustor"
# ----------------------------------------------------------------
# 4. ollama-metrics (NorskHelsenett) — Ollama LLM metrics
# รัน บน Desk-5439 (192.168.10.100) ตาม ADR-023A
# sidecar expose /metrics บน port 9924
# ============================================
# QNAP Metrics (Remote - 192.168.10.8)
# ============================================
# Host metrics from Node Exporter (QNAP)
- job_name: "qnap-node"
static_configs:
- targets: ["192.168.10.8:9100"]
labels:
host: "qnap"
# Container metrics from cAdvisor (QNAP)
- job_name: "qnap-cadvisor"
static_configs:
- targets: ["192.168.10.8:8088"]
labels:
host: "qnap"
# Backend NestJS application (QNAP)
- job_name: "backend"
static_configs:
- targets: ["192.168.10.8:3000"]
labels:
host: "qnap"
metrics_path: "/metrics"
# MariaDB Exporter (optional - QNAP)
- job_name: "mariadb"
static_configs:
- targets: ["192.168.10.8:9104"]
labels:
host: "qnap"
# ============================================
# Desk-5439 Metrics (Remote - 192.168.10.100)
# ============================================
# ollama-metrics (NorskHelsenett) — Ollama LLM metrics
# sidecar รันบน Desk-5439 ตาม ADR-023A, expose /metrics บน port 9924
#
# Metrics ที่ collect:
# ollama_prompt_tokens_total — prompt tokens รวม
# ollama_generated_tokens_total — generated tokens รวม
# ollama_request_duration_seconds — latency histogram
# ollama_time_per_token_seconds — inference speed
# ollama_loaded_models — จำนวน model ใน VRAM
# ollama_model_loaded — 1/0 per model
# ollama_model_ram_mb — VRAM usage (MB) per model
# ----------------------------------------------------------------
- job_name: 'ollama-metrics'
scrape_interval: 30s # Ollama metrics ไม่เปลี่ยนเร็ว — 30s เพียงพอ
# Metrics ที่ collect:
# ollama_prompt_tokens_total — prompt tokens รวม
# ollama_generated_tokens_total — generated tokens รวม
# ollama_request_duration_seconds — latency histogram
# ollama_time_per_token_seconds — inference speed (tok/s)
# ollama_loaded_models — จำนวน model ใน VRAM
# ollama_model_loaded — 1/0 per model
# ollama_model_ram_mb — VRAM usage (MB) per model
- job_name: "ollama-metrics"
scrape_interval: 30s
static_configs:
- targets: ['192.168.10.100:9924']
- targets: ["192.168.10.100:9924"]
labels:
host: 'desk-5439'
service: 'ollama'
role: 'ai-inference'
# ----------------------------------------------------------------
# 5. Loki — Log aggregation health (ASUSTOR)
# ----------------------------------------------------------------
- job_name: 'loki'
static_configs:
- targets: ['loki:3100']
labels:
host: 'asustor'
service: 'loki'
host: "desk-5439"
service: "ollama"
role: "ai-inference"