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GeoNetAgent, LDAPWeb, server-audit, server-connection
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LDAPWeb/server-connection/geonet-console/docs/ai-session-summary.md

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AI Session Summary — geonet-console

session: 2026-07-06-ai-chat-endpoint
project: server-connection/geonet-console
version: ai-fase3
status: deployed
next: UI chat Super Apps PWA + user memory + ai.chat permission guard
agent: Cascade
branch: main

TL;DR

  • POST /api/v1/ai/chat + GET /api/v1/ai/status live di production (console.gisportal.id)
  • RAG pipeline: embed query → pgvector 10.100.1.24:5433 → 5 context chunks → Ollama 10.100.1.14:11434 → jawaban
  • Verified: query "route untuk feedback" → jawab POST /api/v1/feedback dengan akurat

Files baru

File Fungsi
app/Services/AiChatService.php Embed query, similarity search pgvector, generate via Ollama
app/Http/Controllers/Api/V1/AiChatController.php Handler POST /api/v1/ai/chat + GET /api/v1/ai/status
config/pgvector.php Config pgvector — baca env PGVECTOR_HOST/PORT/DB/USER/PASSWORD

Files dimodifikasi

File Perubahan
config/ollama.php Default URL → 10.100.1.14:11434, model → qwen2.5-coder:14b
routes/api.php Tambah 2 route AI Chat, import AiChatController

Env vars baru di server .env

OLLAMA_BASE_URL=http://10.100.1.14:11434
OLLAMA_CHAT_MODEL=qwen2.5-coder:14b
OLLAMA_EMBED_MODEL=nomic-embed-text
PGVECTOR_HOST=10.100.1.24
PGVECTOR_PORT=5433
PGVECTOR_DB=geonet_project_search
PGVECTOR_USER=geonet_ai
PGVECTOR_PASSWORD=<lihat .env server>

API endpoint

Method Path Auth Keterangan
GET /api/v1/ai/status Bearer Cek ketersediaan + model aktif
POST /api/v1/ai/chat Bearer Chat dengan RAG codebase

Request body /ai/chat:

{
  "message": "pertanyaan...",
  "history": [{"role":"user","content":"..."},{"role":"assistant","content":"..."}]
}

Deploy notes

  • Image di-rebuild di 10.100.1.24 via docker compose build geonet-console
  • Bug: jangan gunakan scp config/*.php routes/api.php root@host:/path/config/ dalam satu perintah — routes/api.php akan tertimpa ke config/api.php
  • Selalu deploy config dan routes terpisah

Lanjut dari sini

  1. UI chat di Super Apps PWA — React window, kirim ke /api/v1/ai/chat
  2. User memory — POST /api/v1/ai/memory, simpan ke tabel user_memory di pgvector
  3. Permission guard — tambah ai.chat ke group_permissions, guard di middleware
  4. Streaming — opsional, tambah stream: true ke OllamaService::chat()

Jangan

  • Jangan hardcode PGVECTOR_PASSWORD di source — baca dari env
  • Jangan expose /api/v1/ai/chat tanpa auth (api.auth middleware sudah aktif)
  • Jangan rebuild image tanpa verifikasi config/api.php isi yang benar