Files
microdao-daarion/QUICKSTART_PHASE3.md
Apple 6bd769ef40 feat(city-map): Add 2D City Map with coordinates and agent presence
- Add migration 013_city_map_coordinates.sql with map coordinates, zones, and agents table
- Add /city/map API endpoint in city-service
- Add /city/agents and /city/agents/online endpoints
- Extend presence aggregator to include agents[] in snapshot
- Add AgentsSource for fetching agent data from DB
- Create CityMap component with interactive room tiles
- Add useCityMap hook for fetching map data
- Update useGlobalPresence to include agents
- Add map/list view toggle on /city page
- Add agent badges to room cards and map tiles
2025-11-27 07:00:47 -08:00

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# ⚡ QUICKSTART: Phase 3 — LLM + Memory + Tools
**One-task start for real agent intelligence**
---
## 🎯 What Phase 3 Adds
| Before (Phase 2) | After (Phase 3) |
|------------------|-----------------|
| Mock LLM responses | Real GPT-4/DeepSeek/Local |
| No memory | RAG with vector search |
| No tools | Tool execution (projects, tasks, etc.) |
---
## 🚀 One-Command Start
```bash
# Copy Phase 3 master task
cat docs/tasks/PHASE3_MASTER_TASK.md | pbcopy
# Paste into Cursor AI
# Press Enter
# Wait ~2-3 hours
```
**Cursor will create:**
- ✅ llm-proxy (10 files)
- ✅ memory-orchestrator (9 files)
- ✅ toolcore (8 files)
- ✅ docker-compose updates
- ✅ agent-runtime integration
---
## 🔑 Prerequisites
### 1. OpenAI API Key (or Local LLM)
**Option A: OpenAI**
```bash
export OPENAI_API_KEY="sk-..."
```
**Option B: Local LLM (Ollama)**
```bash
# Install Ollama
curl https://ollama.ai/install.sh | sh
# Pull model
ollama pull qwen2.5:8b
# Run server
ollama serve
```
### 2. Vector Database
**Option A: pgvector (PostgreSQL extension)**
```sql
CREATE EXTENSION IF NOT EXISTS vector;
```
**Option B: Simple stub (Phase 3 OK)**
```
# Memory Orchestrator can work with simple PostgreSQL
# Vector search = stub for Phase 3
```
---
## 📦 After Implementation
### Start Services:
```bash
# If using existing start script
./scripts/start-phase2.sh # Existing services
# Start Phase 3 services
docker-compose -f docker-compose.phase3.yml up -d
```
### Test LLM Proxy:
```bash
curl -X POST http://localhost:7007/internal/llm/proxy \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4.1-mini",
"messages": [
{"role": "user", "content": "Hello!"}
],
"metadata": {
"agent_id": "agent:sofia",
"microdao_id": "microdao:daarion"
}
}'
# Expected: Real GPT-4 response!
```
### Test Memory:
```bash
# Query
curl -X POST http://localhost:7008/internal/agent-memory/query \
-H "Content-Type: application/json" \
-d '{
"agent_id": "agent:sofia",
"microdao_id": "microdao:daarion",
"query": "What did we discuss about Phase 3?",
"limit": 5
}'
```
### Test Tools:
```bash
# List tools
curl http://localhost:7009/internal/tools
# Call tool
curl -X POST http://localhost:7009/internal/tools/call \
-H "Content-Type: application/json" \
-d '{
"tool_id": "projects.list",
"agent_id": "agent:sofia",
"microdao_id": "microdao:daarion",
"args": {}
}'
```
---
## 🧪 E2E Test
### In Messenger UI:
**User:** "Sofia, що нового в проєкті DAARION?"
**Expected Agent Flow:**
1. ✅ Query memory (past discussions)
2. ✅ Call tool: projects.list
3. ✅ Build prompt with context
4. ✅ Call real LLM (GPT-4)
5. ✅ Post rich reply
**Sofia:** "В проєкті DAARION є кілька оновлень:
- Phase 2 Agent Integration завершено ✅
- Phase 3 LLM Proxy в розробці 🔄
- Додано 3 нові агенти
Хочете детальніше по якомусь пункту?"
---
## 📊 Service Status
```bash
# Check all Phase 3 services
docker ps | grep -E '(llm-proxy|memory-orchestrator|toolcore)'
# Check health
curl http://localhost:7007/health # LLM Proxy
curl http://localhost:7008/health # Memory
curl http://localhost:7009/health # Toolcore
# Check logs
docker logs -f llm-proxy
docker logs -f memory-orchestrator
docker logs -f toolcore
```
---
## 🎯 Success Indicators
After Phase 3:
- ✅ Agent uses real LLM (not keyword mock)
- ✅ Agent remembers conversations
- ✅ Agent can execute tools
- ✅ Responses are intelligent & contextual
- ✅ Latency still < 5s
---
## 🐛 Troubleshooting
### LLM Proxy not working?
```bash
# Check API key
docker logs llm-proxy | grep "OPENAI_API_KEY"
# Test provider directly
curl https://api.openai.com/v1/models \
-H "Authorization: Bearer $OPENAI_API_KEY"
```
### Memory not working?
```bash
# Check PostgreSQL connection
docker logs memory-orchestrator | grep "PostgreSQL"
# Check embeddings
docker logs memory-orchestrator | grep "embedding"
```
### Tools not working?
```bash
# Check registry loaded
curl http://localhost:7009/internal/tools
# Check permissions
docker logs toolcore | grep "allowed_agents"
```
---
## 📚 Documentation
- [PHASE3_MASTER_TASK.md](docs/tasks/PHASE3_MASTER_TASK.md) — Complete spec
- [PHASE3_READY.md](PHASE3_READY.md) — Overview
- [PHASE3_ROADMAP.md](docs/tasks/PHASE3_ROADMAP.md) — Detailed plan
---
## 🔜 Next Steps
After Phase 3 works:
1. Test with multiple agents
2. Add more tools (task.create, followup.create)
3. Tune memory relevance
4. Optimize LLM costs
5. Monitor usage
---
**Time to Start:** Copy PHASE3_MASTER_TASK.md into Cursor! 🚀
**Questions?** Check [PHASE3_READY.md](PHASE3_READY.md) first.