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3.2 KiB
3.2 KiB
TODO — Ollama
Last updated: 2026-07-06
High Priority
Fase 1 — GPU Node (PC-Multimedia) ✅ SELESAI
- CUDA 12.9 sudah tersedia via driver 576.88 (tidak perlu install terpisah)
- Install Ollama v0.31.1 di Windows (
OllamaSetup.exe) - Set
OLLAMA_MODELS=T:\ollama\models+OLLAMA_HOST=0.0.0.0:11434viasetx /M - Autostart via Task Scheduler (SYSTEM, AtStartup) — script
PC-Multimedia/scripts/install-ollama-task.ps1 - Firewall rule
OllamaVLAN: TCP 11434 dari10.100.1.0/24only - Pull
qwen2.5-coder:14b(9.0 GB) +nomic-embed-text(274 MB) →T:\ollama\models - Verified: API
http://10.100.1.14:11434reachable, VRAM 11.5 GB / 16 GB saat loaded
Fase 2 — pgvector + Codebase Index ✅ SELESAI
- pgvector Docker di
10.100.1.24:5433(pgvector 0.8.4 / pg16) - DB
geonet_project_search+ tabelcode_chunks+user_memory+ index HNSW - Script indexer
Ollama/indexer/indexer.py— 1.784 chunks dari 1.031 files, 18 repo - Verified: similarity search akurat (query → FeedbackController.php sebagai top result)
Fase 3 — Integrasi geonet-console ✅ SELESAI
OLLAMA_BASE_URL=http://10.100.1.14:11434di geonet-console.envAiChatService— embed query → pgvector similarity search → inject context → Ollama chatAiChatController—POST /api/v1/ai/chat+GET /api/v1/ai/statusconfig/pgvector.php— config PGVECTOR_HOST/PORT/DB/USER/PASS- Verified end-to-end: 5 context chunks retrieved, jawaban akurat tentang route feedback
- User memory: simpan pola interaksi per user (next iteration)
VM .26 (tetap jalan sebagai fallback)
- Tetap running
qwen2.5:7b+nomic-embed-textsebagai fallback CPU inference - SMB read-only mount QNAP
10.100.1.10di VM.26(indexer background)
Medium Priority
- UI chat di Super Apps PWA — window chat terintegrasi
- User memory / RAG: retrieve pola kebiasaan user saat generate response
- Deploy agent (Fase 4): tool calling SSH + docker exec untuk bantu deploy
- Healthcheck / monitoring (Zabbix atau cron
ollama ps) - Optimasi VM
.26: Ubuntu Desktop → Server atau matikan GUI (hemat RAM)
Low Priority
- Fine-tuning LoRA untuk template spesifik organisasi (butuh 1000+ contoh data)
- Evaluasi model
deepseek-coder-v2:16buntuk coding tasks - Backup
/data/ollama/modelske QNAP - Dokumentasi troubleshooting inference timeout
- Migrasi model ke VM
.26jika PC-Multimedia tidak bisa 24/7
Selesai (Sesi Ini)
- Audit live VM
10.100.1.26— Ollama + model verified - Bootstrap dokumentasi repo
Ollama/(AI-Agent-Standards) - Daftar di
Workspace-Context.md - Audit hardware PC-Multimedia via DxDiag — Core Ultra 7 265K, 64 GB, RTX 5060 Ti
- Diskusi arsitektur AI onprem: Context Injection → RAG/Memory → Fine-tuning
- Diskusi AI coding assistant + deploy agent on-premise
- Fase 1 GPU Node PC-Multimedia — Ollama v0.31.1, GPU inference aktif, verified dari laptop
- Fase 2 pgvector — Docker
10.100.1.24:5433, 1.784 chunks, similarity search verified - Fase 3 integrasi —
POST /api/v1/ai/chatlive, RAG end-to-end verified di geonet-console