AGMind

Private RAG platform for NVIDIA DGX Spark — one command, production-ready

Quick Start · Architecture · Cluster · Operations · Troubleshooting · 🇷🇺 Русский

Important

Supported platform: aarch64 / NVIDIA GB10 (DGX Spark and equivalents). Since 2026-04-25, x86_64 support has been removed — install.sh exits 1 on other architectures. Override: AGMIND_ALLOW_AMD64=true (no guarantees — NGC vLLM and Docling cu130 ship arm64-only manifests).

📖 Overview

AGMind is a one-command installer for a private RAG platform on NVIDIA DGX Spark (GB10, 128 GB unified memory). It deploys 30+ containers via Docker Compose: Dify + vLLM + Weaviate/Qdrant + RAGFlow + Docling + monitoring, with an interactive wizard, hardware autodetection, and optional dual-Spark clustering over 200G QSFP.

sudo bash install.sh

Built for: DevOps engineers, ML teams, and IT departments running a private AI stack on DGX Spark hardware — no vendor lock-in, no cloud egress.

Why AGMind

⚡ One command, ~30 minutes to a working stack — wizard → configs → image pull → start → admin user → final URL screen. No manual YAML.
🔒 Local models, zero data egress — gemma-4-26B (vLLM) + bge-m3 + bge-reranker run on the GB10. Documents and queries stay on your hardware.
🛡️ Production hardening — UFW + fail2ban + Authelia (optional 2FA), 30+ Linux capabilities dropped, rate limiting, SSRF proxy, secret rotation.
🧠 GB10 unified memory aware — calibrated mem_limit and gpu_memory_utilization for the 121 GiB shared pool; mDNS via avahi for .local resolution; NAT-on-demand for air-gapped peer Spark.
🔧 Day-2 CLI — agmind status / health / backup / update / ragflow / docling bench / plugin-daemon / mdns-status — operations without docker knowledge.

💻 Hardware Requirements

Warning

AGMind targets DGX Spark / GB10 unified memory only. Anything else is unsupported.

Parameter	Required	Notes
Platform	NVIDIA DGX Spark (GB10) or equivalent aarch64 + Blackwell	x86_64 path removed 2026-04-25
OS	DGX OS 7.5.0 (Ubuntu 24.04 LTS arm64)	NVIDIA driver 580.142 — do not upgrade past 580.x
CPU	20-core Grace (ARM Neoverse V2)	—
Memory	128 GB LPDDR5X unified (CPU+GPU shared)	AGMind budgets 121 → 85 GiB for containers; 35 GiB reserved for kernel/swap
GPU	Blackwell SM_121 (60 SM, 4096 CUDA cores)	MIG not available on GB10. FP8 broken in FlashInfer — use `VLLM_ATTENTION_BACKEND=TRITON_ATTN`
Disk	100 GB+ free on `/`	gemma-4 weights ~52 GB, container images ~30 GB
Network	Ethernet for LAN; optional QSFP 200G DAC for dual-Spark	mDNS via avahi requires UDP/5353 free
Docker	29.0+ with NVIDIA Container Toolkit	install.sh installs both

Caution

Do not upgrade NVIDIA driver past 580.x on Spark. Three independent regressions on GB10 unified memory: CUDAGraph capture deadlock, UMA memory leak (~80 GiB ghost), and Blackwell TMA bug in 595.58.03. NVIDIA staff: "we do not support new drivers past 580.126.09 on Spark". Pin: apt-mark hold nvidia-driver-580-open.

🚀 Quick Start

git clone https://github.com/botAGI/AGmind.git
cd AGmind
sudo bash install.sh

The wizard asks 10–15 questions depending on choices (stack mode, LLM model, optional services, security toggles, monitoring). After ~25 minutes the stack is live.

Endpoints (mDNS — no DNS server needed)

Service	URL	Login
Dify App	`http://agmind-dify.local`	`admin@agmind.ai`
Dify Console	`http://agmind-dify.local/console`	(same — see `credentials.txt`)
RAGFlow	`http://agmind-rag.local`	register on first visit
Open WebUI	`http://agmind-chat.local`	(same admin) — optional
LiteLLM Gateway	`http://agmind-litellm.local`	master key in `credentials.txt`
MinIO Console	`http://agmind-storage.local`	creds in `credentials.txt`
Grafana	`http://<spark-ip>:3001`	password in `credentials.txt`
Portainer	`https://<spark-ip>:9443`	first visit creates admin

Note

All credentials live in /opt/agmind/credentials.txt (chmod 600, root-only).

Non-Interactive Install

sudo NON_INTERACTIVE=true \
     LLM_MODEL=gemma-4-26b \
     EMBED_PROVIDER=vllm EMBEDDING_MODEL=bge-m3 \
     ENABLE_RAGFLOW=true \
     bash install.sh

📦 What's Included

Core Stack

Component	Image / Tag	Purpose
Dify	`langgenius/dify-api:1.13.3`	Workflow orchestrator + primary frontend
vLLM (LLM)	`vllm/vllm-openai:gemma4-cu130`	NVIDIA playbook build for arm64 + SM_121
vLLM (embed)	`nvcr.io/nvidia/vllm:26.02-py3`	`bge-m3` embeddings (1024-dim)
vLLM (rerank)	`nvcr.io/nvidia/vllm:26.02-py3`	`bge-reranker-v2-m3`
Docling-serve cu130	`docling-serve-cu130:v1.16.1`	GPU document extractor + OCR + VLM picture-description
PostgreSQL	`postgres:16-alpine3.23`	Dify metadata, plugin state
Redis	`redis:7.4.8-alpine`	Task queue, plugin cache
Weaviate / Qdrant	`semitechnologies/weaviate:1.37.2`	Vector store (Weaviate default)
nginx	`nginx:1.30.0-alpine`	Reverse proxy (variable-form `proxy_pass`)
plugin_daemon	`langgenius/dify-plugin-daemon:0.5.3-local`	Dify plugin runtime

RAGFlow Integration

RAGFlow v0.24.1-spark — deep document parsing + retrieval, image ar2r223/ragflow-spark:v0.24.1-spark (cherry-picked TitleChunker / TokenChunker / 7 ingestion templates from upstream main + multilingual OCR Latin/Cyrillic/Chinese, file metadata in ES chunks, AVIF, Russian VLM prompts for image describe).
Dify ↔ RAGFlow via witmeng/ragflow-api plugin from Dify Marketplace (8K+ installs).
Storage: MySQL + Elasticsearch 9.x + MinIO (S3-compatible).
Toggle: ENABLE_RAGFLOW=true in wizard or env.

Monitoring & Ops

Prometheus + Grafana — 5 dashboards (overview, containers, GPU master, GPU worker, logs). Custom textfile collector for agmind_gpu_* metrics (NVML returns N/A on GB10 unified memory — dcgm-exporter does not work).
Loki + Grafana Alloy (Promtail → Alloy migration, 2026-04). Searchable container logs.
Alertmanager — Telegram / webhook channels.
Portainer 2.36.0 — visual container management (master + auto-deployed agent on peer Spark).
fail2ban + UFW — bruteforce protection, LAN-only firewall by default.

Optional Services

Wizard checklist (click to expand)

Service	RAM	Purpose
Open WebUI	~300 MB	Alternative chat UI at `agmind-chat.local`
LiteLLM	~1 GB	OpenAI-compatible gateway over multiple providers
SearXNG	~256 MB	Private metasearch (Google/Bing/DDG) for Dify agents
DB-GPT	~1 GB	NL2SQL agent + dataset chat
Crawl4AI	~2 GB	Headless Chromium web crawler with REST API
RAGFlow	~13 GB	Deep document parsing + retrieval (see above)
Authelia 2FA	~150 MB	TOTP/WebAuthn for Grafana / Portainer
Open Notebook	~500 MB	BROKEN in v3.0.1 — do not enable

🏗 Architecture

                                Clients (LAN)
                                      │
                                      ▼  mDNS resolution (*.local → 192.168.x.x)
       ┌─────────────────────────────────────────────────────────────────────┐
       │  nginx — variable-form proxy_pass · agmind-*.local server-blocks    │
       │           :80  :443  :3000  :4001 LiteLLM                           │
       └────┬────────┬─────────┬───────────┬──────────────┬──────────────────┘
            │        │         │           │              │
   agmind-dify   agmind-rag  /litellm  /storage     agmind-chat (opt)
   .local (Dify) .local      .local    .local       .local (Open WebUI)
            │        │
            ▼        ▼
       ┌────────────────────────────────────────────────────────────────────┐
       │  Dify (api · worker · web · sandbox · plugin_daemon)               │
       │  RAGFlow (ragflow + mysql + ES) + Dify plugin witmeng/ragflow-api  │
       └────────┬───────────┬───────────┬──────────────────┬────────────────┘
                │           │           │                  │
                ▼           ▼           ▼                  ▼
            Postgres     Redis      Weaviate           MinIO (S3-compat)
            metadata    queues       vectors           agmind-storage.local

  ─── ML inference on GB10 unified memory (121 GiB pool) ───────────────────
   vLLM-embed (NGC 26.02-py3) :8001  bge-m3 1024-dim
   vLLM-rerank (NGC 26.02-py3) :8002  bge-reranker-v2-m3
   Docling-serve cu130        :8765  PDF/DOCX/PPTX → MD + OCR + VLM
   vLLM gemma-4-26B-A4B (cu130)
       single-Spark → shares GPU above, wizard asks ctx 32K/64K/128K
       dual-Spark   → peer 192.168.100.2:8000, dedicated GPU, 128K default

  ─── Monitoring (always on) ────────────────────────────────────────────────
   Prometheus :9090 → Grafana :3001 (5 dashboards)
   Loki + Grafana Alloy (Promtail migrated 2026-04)
   Alertmanager → Telegram / Webhook
   Portainer :9443 — master + auto-deployed agent on peer:9001
   node-exporter + cAdvisor — both nodes; agmind_gpu_* via textfile collector

  ─── Docker networks ───────────────────────────────────────────────────────
   agmind-frontend — nginx ↔ web UIs · Grafana · Portainer
   agmind-backend  — all services east-west
   ssrf-network    — isolated: Dify Sandbox ↔ Squid proxy

Note

Hardcoded SVG diagram in branding/architecture.svg is from v2.x and no longer reflects the stack (Ollama / TEI / Promtail / VPS profile shown there have all been retired). Treat the ASCII above as the source of truth.

Repository Layout

agmind/
├── install.sh                   # Main orchestrator (11 phases)
├── lib/                         # 15 modules: wizard, config, compose, health, security, detect, …
├── scripts/                     # Day-2 CLI: agmind, update, backup, restore, mdns-status, docling-bench, gpu-metrics
├── templates/                   # docker-compose.yml, docker-compose.worker.yml, nginx.conf, env templates, versions.env
├── monitoring/                  # Prometheus, Grafana dashboards, Loki, Alloy, Alertmanager
├── pipelines/                   # Universal Auto-Router DSL (Dify workflows + docling-serve)
├── dify-workflows/              # KB / workflow templates stash
├── plugins/                     # Forked / patched Dify plugins
├── docs/                        # Detailed documentation
└── branding/                    # Logo + theme (architecture.svg outdated, see ASCII above)

Docker Networks

Network	Purpose
`agmind-frontend`	nginx ↔ web UIs, Grafana, Portainer
`agmind-backend`	All services, internal east-west
`ssrf-network`	Isolated: Dify Sandbox ↔ Squid (SSRF-safe egress)

Install Phases

11 phases — click to expand

#	Name	What it does
1	Diagnostics	OS, CPU, GPU, driver, disk, RAM, ports, mDNS prerequisites
2	Wizard	10–15 interactive questions (stack mode, LLM, optionals, security)
3	Docker	Install Docker CE + NVIDIA Container Toolkit (idempotent)
4	Configuration	Generate `.env`, nginx config, secrets, mDNS aliases
5	Pull	Validate manifests (arm64 required) and pull images
6	Start	`docker compose up -d`, create Dify admin, init databases
7	Deploy Peer	Master only: scp worker compose + `.env` to peer, deploy vLLM via SSH
8	Health	Wait for healthchecks, smoke-test critical endpoints
9	Models	Download gemma-4 + bge-m3 + bge-reranker (cached on re-install)
10	Backups	Establish baseline backup + cron schedule
11	Complete	systemd unit, final URL screen + credentials

🌐 Cluster (Dual-Spark)

AGMind supports a two-node configuration: master + peer over QSFP 200G DAC.

  ┌─────────────────────┐                       ┌─────────────────────┐
  │  spark-master       │   QSFP 200G DAC       │  spark-peer         │
  │  (frontend + DB +   │ ◄──── direct link ───►│  (vLLM + heavy GPU  │
  │  Dify + RAGFlow +   │   192.168.100.0/24    │  workloads)         │
  │  monitoring)        │                       │                     │
  │  WAN: ethernet      │                       │  WAN: NAT via       │
  │  iptables MASQUERADE│ ────── default gw ────►│  master QSFP        │
  └─────────────────────┘                       └─────────────────────┘

Capability	Detail
Symmetric install	`sudo bash install.sh` on both nodes; wizard detects QSFP via LLDP, falls back to ping. `--mode=master` / `--mode=worker` for non-interactive
Frontend on master	Dify, RAGFlow, Postgres, Redis, Weaviate, nginx, monitoring all on master. Peer runs only vLLM
vLLM on peer	`LLM_ON_PEER=true` flag in `.env`. Master ↔ peer via OpenAI-compatible HTTP (no LiteLLM router)
NAT on demand	Peer's WAN egress (image pull, model download) goes through master's QSFP gateway via `iptables MASQUERADE`. Air-gap intent preserved when WAN disabled (`agmind nat off`)
Passwordless SSH	Wizard configures master ↔ peer key auth
Monitoring	Two Grafana dashboards (`gpu-master`, `gpu-worker`), peer textfile collector + cron for `agmind_gpu_*`
Portainer agent	`agmind-portainer-agent` auto-deployed on peer with shared `PORTAINER_AGENT_SECRET` (persistent across re-installs)

Tip

Adding peer to master Portainer (one-time manual step): Open https://<master-ip>:9443 → Environments → Add → Agent → URL=<peer_ip>:9001, SECRET from credentials.txt.

⚙️ Configuration

All settings live in /opt/agmind/docker/.env (chmod 600). The wizard populates everything; no manual edits required.

LLM Provider

vLLM is the default and only first-class choice on GB10. Ollama exists as a hidden override (LLM_PROVIDER=ollama) but is gated behind a Compose profile.

Variable	Default	Purpose
`LLM_PROVIDER`	`vllm`	`vllm` (default) or `external` (BYO API)
`VLLM_MODEL`	`gemma-4-26B-A4B-it`	HF-style model id
`VLLM_GPU_MEM_UTIL`	`0.60`	Lower than upstream — leaves headroom for docling-serve (peaks 16 GiB)
`VLLM_MAX_MODEL_LEN`	`65536`	65K context with fp8 KV cache
`VLLM_ATTENTION_BACKEND`	`TRITON_ATTN`	FP8 / FlashInfer broken on SM_121

The Spark wizard offers three paths for vLLM model selection:

Gemma 4 26B-A4B (NVIDIA playbook default — recommended)
Curated list — Qwen / Llama / Mistral / phi-4 with VRAM hints
Custom HuggingFace model — input field, e.g. meta-llama/Llama-3.1-70B-Instruct

Note

On dual-Spark the context question is skipped — peer has dedicated GPU → 128K default. On single-Spark the wizard asks 32K / 64K / 128K because vLLM shares GPU with docling.

Optional Service Toggles

ENABLE_OPENWEBUI, ENABLE_LITELLM, ENABLE_DOCLING, ENABLE_SEARXNG, ENABLE_DBGPT, ENABLE_CRAWL4AI, ENABLE_RAGFLOW, ENABLE_AUTHELIA, ENABLE_DIFY_PREMIUM, ENABLE_MINIO. All set by the wizard; override via env for non-interactive installs.

Image Versions

All image tags pinned in templates/versions.env. The :latest tag is forbidden. Each tag must have an arm64 manifest verified via docker manifest inspect.

bash tests/compose/test_image_tags_exist.sh   # CI test

🛠 Operations

Status & Diagnostics

agmind status [--json]               # Services, GPU, models, endpoints
agmind doctor [--peer]               # System diagnostics
agmind health                        # Alias for doctor
agmind logs [-f] <service>           # Tail container logs
agmind mdns-status                   # Verify avahi publishing for *.local

Lifecycle

agmind stop                          # Stop all containers
agmind start                         # Start configured services
agmind restart                       # Restart all
agmind upgrade --diff                # Compare pinned versions vs running
agmind update [--check|--auto]       # Update stack from main branch

GPU & Models

agmind gpu status                    # Loaded models, VRAM, utilization
agmind gpu assign <svc> <id>         # Pin service to GPU id
agmind model list                    # All loaded models (vLLM endpoints)

RAGFlow

agmind ragflow status                # 3 ragflow containers state
agmind ragflow query <text>          # Test retrieval
agmind ragflow es-health             # Elasticsearch cluster health

Plugin Daemon & Marketplace

agmind plugin-daemon status          # State + health
agmind plugin-daemon stop|start      # Toggle (root) — Dify plugins stop working when off
agmind plugin-daemon logs            # Tail logs

agmind plugins status                # ONLINE / OFFLINE
agmind plugins online                # Enable marketplace.dify.ai (default)
agmind plugins offline               # Local .difypkg only (supply-chain hardened)

Performance

agmind loadtest list                 # k6 scenarios
agmind loadtest chat --vus 8         # Concurrent chat load test
agmind docling bench <pdf>           # Cold/warm/per-page timing for any PDF

Backup & Restore

sudo agmind backup                   # PostgreSQL + Redis + volumes
sudo agmind restore <path>           # Restore from backup
sudo agmind rotate-secrets           # Regenerate passwords/keys
sudo agmind uninstall [--keep-models]  # Remove stack

📁 Server Layout

/opt/agmind/
├── docker/
│   ├── .env                         # Secrets and config (chmod 600)
│   ├── docker-compose.yml           # All services
│   ├── nginx/nginx.conf             # Reverse proxy
│   └── volumes/                     # Postgres, Redis, vectors, models, MinIO
├── credentials.txt                  # All passwords (chmod 600)
├── scripts/                         # CLI + utilities (mirrored from repo)
├── templates/                       # init SQL, env templates
├── monitoring/                      # Prometheus rules, Grafana dashboards
├── docs/                            # Citations, alerts, docling, RAGFlow
└── install.log                      # Full install transcript

🩺 Troubleshooting

Symptom	First check
Service stuck unhealthy	`agmind logs <service>` — last 50 lines tell the story
Dify Console 502	`docker restart agmind-nginx` (then verify nginx config uses variable-form `proxy_pass`)
Model not loading	`nvidia-smi` + `docker logs agmind-vllm` — usually OOM or driver mismatch
`agmind-rag.local` unresolved	`agmind mdns-status` — checks for second mDNS responder on UDP/5353
Indexing stuck after recreate	`redis-cli DEL generate_task_belong:* celery-task-meta-*` then `docker restart agmind-worker agmind-api`
502 on every request	full `agmind doctor` — fail2ban / UFW / GPU driver health
Disk full	`docker system prune -a` then `agmind backup` and prune `/var/backups/agmind/`
DR-grade restore	`agmind restore /var/backups/agmind/<latest>/`

Tip

Detailed runbooks for known gotchas live in docs/. Open an issue if you hit something missing — we backfill the runbook.

✅ Definition of Done

A change is only complete when these checks pass green:

# Bash hygiene
shellcheck -S warning lib/*.sh scripts/*.sh install.sh

# Compose schema + image existence
cd /opt/agmind/docker && sudo docker compose config | grep 'image:' | sort -u
bash tests/compose/test_image_tags_exist.sh core/compose.yml

# Live health
sudo docker ps --format '{{.Names}} {{.Status}}' | grep -v 'healthy\|Up'   # must be empty
avahi-resolve -n agmind-dify.local                                          # must resolve
curl -sf http://agmind-dify.local/console/api/setup                         # must 200

All checks must pass before a PR is mergeable.

📊 Benchmarks

Results on NVIDIA DGX Spark (GB10, 128 GB unified memory):

Metric	gemma-4-26B-A4B-it (MoE)
TTFT (streaming)	183 ms
TPS (single request)	23–24 tokens/sec
TPS (3 concurrent)	50 tokens/sec aggregate
Long generation (500 tok)	20.6s @ 24.3 TPS
Context window	65K tokens (fp8 KV cache)
Max concurrency @ 65K	45 parallel requests
Memory: model weights	48.5 GiB (bfloat16)
Memory: KV cache	41.7 GiB (fp8)
Total footprint	~95 GiB

Docling (5-page arxiv PDF, warm): 6.04s, 0.32s/page, ~1.6 GiB GPU memory.

🗺 Roadmap & Status

v3.0.2 (current) — RAGFlow upgrade to v0.24.1-spark (TitleChunker / TokenChunker + 7 ingestion templates + Russian VLM prompts), Pipeline framework patches.
v3.0.1 — mDNS hardening, dual-Spark cluster, master/worker wizard, NAT-on-demand peer, Portainer peer agent.
2026-04-26 — RAGFlow integrated via DockerHub ar2r223/ragflow-spark.
2026-04-25 — Yellow-zone version bumps (7/8 components arm64 re-verified). x86_64 path retired.
Next — TUI in agmind update (toggle new tools introduced in updates), AGmind workspace plugin (waifu fork), pipeline templates stash.

🤝 Contributing

Work on main only — no feature branches, no merge commits. PRs are cut from main on demand.
Every PR must pass Definition of Done and tests/compose/test_image_tags_exist.sh.
Image tag bumps require docker manifest inspect <image>:<tag> | grep arm64 evidence in the commit message — LLMs hallucinate registry tags.

📜 License

Apache License 2.0

🇷🇺 Русская документация

Развернуть полный перевод (click to expand)

📖 Обзор

AGMind — установщик приватной RAG-платформы для NVIDIA DGX Spark (GB10, 128 GB unified memory). Одной командой разворачивает 30+ контейнеров через Docker Compose: Dify + vLLM + Weaviate/Qdrant + RAGFlow + Docling + мониторинг, с интерактивным визардом, автодетектом железа и опциональным dual-Spark кластером по 200G QSFP.

sudo bash install.sh

Для кого: DevOps-инженеры, ML-команды, IT-отделы, которым нужен приватный AI-стек на DGX Spark — без vendor lock-in и облачного egress.

Зачем AGMind

⚡ Одна команда, ~30 минут до рабочего стека
🔒 Локальные модели, нулевой egress — gemma-4 + bge-m3 локально
🛡️ Production hardening — UFW + fail2ban + Authelia 2FA + drop caps
🧠 GB10-aware бюджеты памяти — 121 GiB unified pool, mDNS, NAT-on-demand
🔧 Day-2 CLI — agmind status / health / backup / update / ragflow

💻 Требования к железу

[!WARNING] AGMind рассчитан только на DGX Spark / GB10. Всё остальное не поддерживается.

Параметр	Требуется	Замечания
Платформа	NVIDIA DGX Spark (GB10)	x86_64 удалён 2026-04-25
ОС	DGX OS 7.5.0 (Ubuntu 24.04 LTS arm64)	Driver 580.142 — не обновлять выше 580.x
CPU	20-ядерный Grace (ARM Neoverse V2)	—
RAM	128 GB LPDDR5X unified	AGMind резервирует 121 → 85 GiB
GPU	Blackwell SM_121 (60 SM)	MIG недоступен; FP8 FlashInfer сломан
Диск	100 GB+ свободно	gemma-4 ~52 GB, образы ~30 GB
Сеть	Ethernet (LAN) + опционально QSFP 200G DAC	mDNS требует UDP/5353
Docker	29.0+ с NVIDIA Container Toolkit	install.sh ставит сам

[!CAUTION] Не обновлять NVIDIA driver выше 580.x. Три регрессии на GB10: CUDAGraph deadlock, UMA leak ~80 GiB, TMA bug 595.58.03. NVIDIA staff: "we do not support new drivers past 580.126.09 on Spark".

🚀 Быстрый старт

git clone https://github.com/botAGI/AGmind.git
cd AGmind
sudo bash install.sh

Визард задаст 10–15 вопросов в зависимости от выборов. Через ~25 минут стек поднят.

Эндпоинты (через mDNS)

Сервис	URL	Логин
Dify App	`http://agmind-dify.local`	`admin@agmind.ai`
Dify Console	`http://agmind-dify.local/console`	(та же — см. `credentials.txt`)
RAGFlow	`http://agmind-rag.local`	регистрация при первом входе
Open WebUI	`http://agmind-chat.local`	(тот же admin) — опционально
LiteLLM Gateway	`http://agmind-litellm.local`	master key в `credentials.txt`
MinIO Console	`http://agmind-storage.local`	креды в `credentials.txt`
Grafana	`http://<spark-ip>:3001`	пароль в `credentials.txt`
Portainer	`https://<spark-ip>:9443`	первый вход создаёт admin

Неинтерактивная установка

sudo NON_INTERACTIVE=true \
     LLM_MODEL=gemma-4-26b \
     EMBED_PROVIDER=vllm EMBEDDING_MODEL=bge-m3 \
     ENABLE_RAGFLOW=true \
     bash install.sh

🌐 Кластер (Dual-Spark)

Поддержка двух DGX Spark машин: master + peer по QSFP 200G DAC.

Возможность	Деталь
Симметричная установка	`sudo bash install.sh` на обеих нодах
Фронтенд на master	Dify, RAGFlow, Postgres, Redis, Weaviate, мониторинг
vLLM на peer	`LLM_ON_PEER=true` в `.env`
NAT on demand	Peer выходит в WAN через QSFP master'а
Passwordless SSH	Визард настраивает обоюдный key auth
Мониторинг	2 дашборда Grafana (`gpu-master`, `gpu-worker`)
Portainer agent	`agmind-portainer-agent` авто-деплоится на peer

[!TIP] Добавление peer в master Portainer (один ручной шаг): Открой https://<master-ip>:9443 → Environments → Add → Agent → URL=<peer_ip>:9001, SECRET из credentials.txt.

⚙️ Конфигурация

В визарде на DGX Spark предлагается 3 пути выбора модели vLLM:

Gemma 4 26B-A4B (рекомендуемый default — NVIDIA playbook)
Общий список (Qwen / Llama / Mistral / phi-4 с оценкой VRAM)
Своя HuggingFace модель (поле ввода — например meta-llama/Llama-3.1-70B-Instruct)

[!NOTE] На dual-Spark вопрос про контекст пропускается (peer имеет dedicated GPU → 128K по умолчанию). На single-Spark спрашивается 32K / 64K / 128K, так как vLLM делит GPU с docling.

Toggle опциональных сервисов

ENABLE_OPENWEBUI, ENABLE_LITELLM, ENABLE_DOCLING, ENABLE_SEARXNG, ENABLE_DBGPT, ENABLE_CRAWL4AI, ENABLE_RAGFLOW, ENABLE_AUTHELIA, ENABLE_DIFY_PREMIUM, ENABLE_MINIO.

🛠 Эксплуатация

# Статус
agmind status [--json]
agmind doctor [--peer]
agmind logs [-f] <service>

# GPU
agmind gpu status
agmind model list

# RAGFlow
agmind ragflow status
agmind ragflow query <text>

# Plugin daemon
agmind plugin-daemon status|stop|start|restart|logs
agmind plugins status|online|offline       # marketplace.dify.ai toggle

# Производительность
agmind loadtest chat --vus 8
agmind docling bench <pdf>

# Бэкапы
sudo agmind backup
sudo agmind restore <path>
sudo agmind rotate-secrets

🩺 Troubleshooting

Симптом	Первая проверка
Сервис висит unhealthy	`agmind logs <service>`
Dify Console 502	`docker restart agmind-nginx`
Модель не грузится	`nvidia-smi` + `docker logs agmind-vllm`
`.local` не резолвится	`agmind mdns-status`
Индексация висит после recreate	`redis-cli DEL generate_task_belong:* celery-task-meta-*`
Полный диск	`docker system prune -a`
Восстановление	`agmind restore /var/backups/agmind/<latest>/`

Подробные runbook'и для известных граблей — в docs/.

📊 Бенчмарки

Метрика	gemma-4-26B-A4B-it (MoE)
TTFT (streaming)	183 ms
TPS (1 запрос)	23–24 tokens/sec
TPS (3 параллельных)	50 tokens/sec aggregate
Контекст	65K (fp8 KV cache)
Max concurrency @ 65K	45 параллельных запросов
Память: веса	48.5 GiB (bfloat16)
Память: KV cache	41.7 GiB (fp8)
Общий footprint	~95 GiB

Docling (5 страниц arxiv PDF, warm): 6.04s, 0.32s/page.

🤝 Контрибьюции

Работа только в main. PR из main по запросу.
Каждый PR обязан проходить DoD и tests/compose/test_image_tags_exist.sh.
Bump тега образа = свидетельство docker manifest inspect <image>:<tag> | grep arm64 в commit message.

Name		Name	Last commit message	Last commit date
Latest commit History 630 Commits
.github		.github
branding		branding
docs		docs
lib		lib
monitoring		monitoring
scripts		scripts
templates		templates
tests		tests
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
COMPATIBILITY.md		COMPATIBILITY.md
COMPONENTS.md		COMPONENTS.md
DR-POLICY.md		DR-POLICY.md
LICENSE		LICENSE
README.md		README.md
RELEASE		RELEASE
install.sh		install.sh

Folders and files

Latest commit

History

Repository files navigation

AGMind

📖 Overview

Why AGMind

💻 Hardware Requirements

🚀 Quick Start

Endpoints (mDNS — no DNS server needed)

Non-Interactive Install

📦 What's Included

Core Stack

RAGFlow Integration

Monitoring & Ops

Optional Services

🏗 Architecture

Repository Layout

Docker Networks

Install Phases

🌐 Cluster (Dual-Spark)

⚙️ Configuration

LLM Provider

Optional Service Toggles

Image Versions

🛠 Operations

Status & Diagnostics

Lifecycle

GPU & Models

RAGFlow

Plugin Daemon & Marketplace

Performance

Backup & Restore

📁 Server Layout

🩺 Troubleshooting

✅ Definition of Done

📊 Benchmarks

🗺 Roadmap & Status

🤝 Contributing

📜 License

🇷🇺 Русская документация

📖 Обзор

Зачем AGMind

💻 Требования к железу

🚀 Быстрый старт

Эндпоинты (через mDNS)

Неинтерактивная установка

🌐 Кластер (Dual-Spark)

⚙️ Конфигурация

Toggle опциональных сервисов

🛠 Эксплуатация

🩺 Troubleshooting

📊 Бенчмарки

🤝 Контрибьюции

📜 Лицензия

About

Topics

Resources

License

Uh oh!

Stars

Watchers

Forks

Releases

Packages 0

Uh oh!

Contributors

Uh oh!

Languages

Packages