DAARWIZZ - AI Agent for DAARION.city

DAARWIZZ is the official AI agent for the DAARION.city ecosystem, designed to help community members navigate microDAO processes, understand roles, and interact with the DAGI Stack.

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🎯 What is DAARWIZZ?

DAARWIZZ is an intelligent agent that: - Guides users through microDAO operations - Explains roles and permissions (RBAC) - Answers questions about DAO processes - Provides onboarding for new members - Enforces security by respecting user entitlements

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🧠 Personality & Behavior

Core Traits

• Helpful: Provides practical, actionable guidance
• Concise: Avoids unnecessary explanations
• Security-aware: Respects RBAC permissions
• Honest: Admits when it doesn't know something
• Professional yet friendly: Approachable but not casual

Style Guidelines

• Short paragraphs, no fluff
• Step-by-step instructions when needed
• Uses numbered lists for procedures
• Always considers user's role and permissions

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📋 System Prompt

DAARWIZZ's behavior is defined by its system prompt located at:

gateway-bot/daarwizz_prompt.txt

Key elements: 1. Identity: Official DAARION.city AI agent 2. Role: Help with microDAO, roles, processes 3. Context awareness: Uses dao_id, user_id, RBAC data 4. Limitations: No legal/financial/medical advice 5. Knowledge boundaries: Only DAARION/microDAO topics

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🔄 How DAARWIZZ Works

Message Flow

User (Telegram)
    ↓ "Привіт! Що це за DAO?"
Gateway (:9300)
    ↓ Load daarwizz_prompt.txt
    ↓ Build request with agent="daarwizz"
Router (:9102)
    ↓ Fetch RBAC context
RBAC (:9200)
    ↓ role: member, entitlements: [chat, vote, comment]
Router
    ↓ Inject RBAC + system_prompt
LLM Provider (Ollama/OpenAI)
    ↓ Generate response with full context
Gateway
    ↓ Send to Telegram
User receives answer

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🛠️ Technical Implementation

Gateway Integration

File: gateway-bot/http_api.py

# Load DAARWIZZ prompt on startup
DAARWIZZ_SYSTEM_PROMPT = load_daarwizz_prompt()

# Build request to Router
router_request = {
    "prompt": text,
    "mode": "chat",
    "agent": "daarwizz",  # Agent identifier
    "metadata": {
        "dao_id": "greenfood-dao",
        "user_id": "tg:12345",
        ...
    },
    "context": {
        "agent_name": "DAARWIZZ",
        "system_prompt": DAARWIZZ_SYSTEM_PROMPT,
        # RBAC injected by Router
    },
}

LLM Provider Support

File: providers/llm_provider.py

def _get_system_prompt(self, req: RouterRequest) -> Optional[str]:
    # 1. Check context.system_prompt (from Gateway)
    context = req.payload.get("context") or {}
    if "system_prompt" in context:
        return context["system_prompt"]

    # 2. Agent-specific fallback
    if req.agent == "daarwizz":
        return "Ти — DAARWIZZ, AI-агент DAARION.city..."

    return None

Docker Configuration

File: gateway-bot/Dockerfile

# Copy DAARWIZZ prompt
COPY gateway-bot/daarwizz_prompt.txt /app/gateway-bot/daarwizz_prompt.txt

ENV DAARWIZZ_NAME=DAARWIZZ
ENV DAARWIZZ_PROMPT_PATH=/app/gateway-bot/daarwizz_prompt.txt

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📖 Example Interactions

Basic Greeting

User: Привіт! Хто ти?

DAARWIZZ:

Привіт! Я — DAARWIZZ, AI-агент екосистеми DAARION.city. 

Я допомагаю учасникам розібратися з:
• microDAO та їх структурою
• Ролями і правами доступу (RBAC)
• Процесами голосування та пропозиціями
• Завданнями та винагородами

Чим можу допомогти?

Role Information

User: Які у мене права в цьому DAO?

DAARWIZZ (with RBAC context):

У greenfood-dao ти маєш роль: member

Твої права (entitlements):
1. chat_access - писати в чат
2. read_proposals - читати пропозиції
3. vote - голосувати за пропозиції
4. comment - коментувати

Для більших прав (наприклад, створення пропозицій) потрібна роль contributor або вища.

Onboarding

User: Як розпочати роботу в DAO?

DAARWIZZ:

Ласкаво просимо! Ось кроки для старту:

1. Ознайомся з документацією DAO (команда /docs)
2. Переглянь активні пропозиції (/proposals)
3. Познайомся з командою в чаті
4. Виконай перше завдання (/tasks)
5. Накопичуй репутацію для підвищення ролі

Твоя поточна роль: guest
Наступна роль: member (після 1 виконаного завдання)

Є питання? Запитуй!

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🎛️ Customization

Updating System Prompt

1. Edit prompt file: bash nano gateway-bot/daarwizz_prompt.txt

2. Rebuild Gateway: bash docker-compose build gateway docker-compose restart gateway

3. Verify loading: bash docker-compose logs gateway | grep "DAARWIZZ system prompt loaded"

Environment Variables

# .env
DAARWIZZ_NAME=DAARWIZZ
DAARWIZZ_PROMPT_PATH=/app/gateway-bot/daarwizz_prompt.txt

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🧪 Testing DAARWIZZ

Local Test (curl)

curl -X POST http://localhost:9300/telegram/webhook \
  -H "Content-Type: application/json" \
  -d '{
    "message": {
      "message_id": 1,
      "from": {"id": 12345, "username": "testuser"},
      "chat": {"id": 12345, "type": "private"},
      "text": "Привіт! Хто ти?"
    }
  }'

Telegram Bot

1. Set up webhook: bash curl -X POST "https://api.telegram.org/bot$TELEGRAM_BOT_TOKEN/setWebhook" \ -d "url=https://your-domain.com/telegram/webhook"

2. Send message to bot in Telegram

3. Check logs: bash docker-compose logs -f gateway router

Expected Log Output

gateway | INFO: DAARWIZZ system prompt loaded (1243 chars)
gateway | INFO: Telegram message from testuser (tg:12345): Привіт! Хто ти?
gateway | INFO: Sending to Router: agent=daarwizz, dao=greenfood-dao
router  | INFO: Received request: mode=chat, agent=daarwizz
router  | INFO: RBAC context: role=member, entitlements=4
router  | INFO: Routing to llm_local_qwen3_8b
router  | INFO: Response generated (345 chars, 2.3s)
gateway | INFO: Telegram message sent to chat 12345

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📊 Metrics & Monitoring

Health Check

curl http://localhost:9300/health

Response:

{
  "status": "healthy",
  "agent": "DAARWIZZ",
  "system_prompt_loaded": true,
  "timestamp": "2024-11-15T14:30:00Z"
}

Performance Targets

Metric	Target	Notes
Prompt loading	< 100ms	On startup
Request enrichment	< 50ms	Gateway processing
End-to-end response	< 5s	Including LLM generation
RBAC lookup	< 100ms	From RBAC service

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🚀 Future Enhancements

Phase 4 Roadmap

1. Knowledge Base Integration
2. Connect to microdao-daarion docs
3. RAG (Retrieval-Augmented Generation)

4. Contextual answers from official docs

5. Multi-language Support

6. Ukrainian (default)
7. English

8. Auto-detect user language

9. Workflow Triggers

10. User: "Onboard me" → triggers CrewAI workflow

11. User: "Review proposal #123" → triggers multi-agent review

12. Analytics

13. Track common questions
14. Identify knowledge gaps

15. Improve prompt iteratively

16. Personalization

17. Remember user context across sessions
18. Adapt responses based on user role
19. Suggest relevant actions

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🔗 Related Documentation

• Gateway Bot
• RBAC Service
• LLM Providers
• Router Configuration

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Version: 0.2.0
Agent: DAARWIZZ
Status: Production-ready ✅
Last Updated: 2024-11-15