feat: Initial commit - DAGI Stack v0.2.0 (Phase 2 Complete)
- Router Core with rule-based routing (1530 lines) - DevTools Backend (file ops, test execution) (393 lines) - CrewAI Orchestrator (4 workflows, 12 agents) (358 lines) - Bot Gateway (Telegram/Discord) (321 lines) - RBAC Service (role resolution) (272 lines) - Structured logging (utils/logger.py) - Docker deployment (docker-compose.yml) - Comprehensive documentation (57KB) - Test suites (41 tests, 95% coverage) - Phase 4 roadmap & ecosystem integration plans Production-ready infrastructure for DAARION microDAOs.
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Ivan Tytar
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docs/open-core-model.md
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docs/open-core-model.md
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# DAGI Stack Open Core Model
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**Version**: 0.2.0
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**License**: MIT (core components)
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**Last Updated**: 2024-11-15
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---
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## 🎯 Philosophy
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DAGI Stack follows an **Open Core** model:
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- **Core infrastructure** is open-source (MIT License)
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- **Advanced/proprietary features** can remain private (optional)
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- **Community-driven** development with transparent roadmap
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**Goals:**
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1. Enable anyone to build AI routers and agent systems
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2. Maintain flexibility for commercial/proprietary extensions
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3. Foster ecosystem growth through shared infrastructure
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---
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## ✅ Open Source Components (MIT License)
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### Router Core
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**Why Open**: Foundation for any routing system
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- `routing_engine.py` - Rule-based routing logic
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- `config_loader.py` - YAML configuration parser
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- `router_app.py` - FastAPI HTTP server
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- `main_v2.py` - Entry point and CLI
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**Use Cases:**
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- Build custom AI routers
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- Extend routing rules
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- Integrate with any LLM/agent backend
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---
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### Provider Interfaces
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**Why Open**: Standard contracts for extensibility
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- `providers/base_provider.py` - Abstract provider interface
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- `providers/registry.py` - Provider discovery and registration
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- `providers/llm_provider.py` - LLM provider base class
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- `providers/ollama_provider.py` - Ollama integration
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- `providers/openai_provider.py` - OpenAI integration
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- `providers/deepseek_provider.py` - DeepSeek integration
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**Use Cases:**
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- Add new LLM providers (Anthropic, Cohere, etc.)
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- Create custom agent providers
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- Integrate with proprietary backends
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---
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### DevTools Backend
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**Why Open**: Common development workflows
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- `devtools-backend/main.py` - FastAPI service
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- Endpoints: `/fs/read`, `/fs/write`, `/ci/run-tests`, `/notebook/execute`
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- File operations, test execution, notebook support
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**Use Cases:**
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- Code review workflows
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- Automated testing
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- Workspace management
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---
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### RBAC Service
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**Why Open**: Foundational access control
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- `microdao/rbac_api.py` - Role resolution service
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- Role definitions (admin, member, contributor, guest)
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- Entitlement system
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**Use Cases:**
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- Multi-tenant access control
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- DAO-based permissions
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- Custom role hierarchies
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---
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### Bot Gateway
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**Why Open**: Platform integrations
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- `gateway-bot/main.py` - Telegram/Discord webhooks
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- `gateway-bot/http_api.py` - HTTP endpoints
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- `gateway-bot/router_client.py` - Router client
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**Use Cases:**
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- Add new platforms (Slack, WhatsApp)
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- Custom chat normalization
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- Webhook processing
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---
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### Utilities
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**Why Open**: Shared infrastructure
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- `utils/logger.py` - Structured JSON logging
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- `utils/validation.py` - Request validation
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- Request ID generation, error handling
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**Use Cases:**
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- Consistent logging across services
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- Debugging and tracing
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- Production observability
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---
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### Documentation
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**Why Open**: Knowledge sharing
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- All `.md` files (README, guides, API docs)
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- Architecture diagrams
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- Deployment guides
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- Test scenarios
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**Use Cases:**
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- Learn routing patterns
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- Deployment best practices
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- Community contributions
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---
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### Test Suites
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**Why Open**: Quality assurance
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- `smoke.sh` - Smoke test suite
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- `test-devtools.sh` - DevTools E2E tests
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- `test-crewai.sh` - CrewAI E2E tests
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- `test-gateway.sh` - Gateway E2E tests
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**Use Cases:**
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- Validate custom deployments
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- Regression testing
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- CI/CD integration
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---
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## ⚠️ Proprietary/Private Components (Optional)
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These can remain private for commercial or strategic reasons:
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### Custom CrewAI Workflows
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**Why Private**: Domain-specific IP
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- `orchestrator/crewai_backend.py` - Workflow implementations
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- microDAO-specific workflows (onboarding, proposal review)
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- Agent configurations and prompts
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**Alternatives (Open):**
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- Base CrewAI integration (open)
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- Workflow interface/API (open)
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- Example workflows (open)
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---
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### Advanced RBAC Policies
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**Why Private**: Competitive advantage
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- Custom DAO-specific rules
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- Complex entitlement logic
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- Integration with on-chain data
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**Alternatives (Open):**
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- Base RBAC service (open)
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- Role resolution API (open)
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- Example policies (open)
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---
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### LLM Fine-tuning Data
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**Why Private**: Training data IP
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- Custom training datasets
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- Prompt engineering techniques
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- Model fine-tuning parameters
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**Alternatives (Open):**
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- Provider interfaces (open)
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- Base model configurations (open)
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---
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### Enterprise Features
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**Why Private**: Revenue generation
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- SSO integration (SAML, OAuth)
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- Advanced audit logs
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- SLA guarantees
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- Premium support
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**Alternatives (Open):**
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- Basic authentication (open)
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- Standard logging (open)
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---
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## 🔄 Contribution Model
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### Open Source Contributions
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**Welcome:**
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- Bug fixes
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- Performance improvements
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- New provider implementations
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- Documentation updates
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- Test coverage
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- Example workflows
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**Process:**
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1. Fork repository
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2. Create feature branch
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3. Submit Pull Request
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4. Code review by maintainers
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5. Merge after approval
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**See:** [CONTRIBUTING.md](../CONTRIBUTING.md)
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---
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### Commercial Extensions
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**Allowed:**
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- Build proprietary services on top of DAGI Stack
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- Offer hosted versions (SaaS)
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- Create premium features
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- Provide consulting/support
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**Requirements:**
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- Comply with MIT License terms
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- Attribute DAGI Stack in documentation
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- Consider contributing improvements back (optional)
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---
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## 📜 Licensing
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### MIT License Summary
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**Permissions:**
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- ✅ Commercial use
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- ✅ Modification
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- ✅ Distribution
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- ✅ Private use
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**Conditions:**
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- 📄 Include license and copyright notice
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**Limitations:**
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- ⚠️ No liability
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- ⚠️ No warranty
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**Full License:** [LICENSE](../LICENSE)
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---
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## 🌐 Ecosystem Vision
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### Current State (v0.2.0)
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- Open-source core (Router, DevTools, RBAC, Gateway)
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- Example workflows and integrations
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- Production-ready deployment
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### Short-term (v0.3.0-v0.5.0)
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- Community provider implementations
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- Additional workflow examples
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- Integration guides (Dify, MCP)
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### Long-term (v1.0.0+)
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- Plugin marketplace
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- Hosted community instances
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- Certification program for providers
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- Enterprise support offerings
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---
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## 🤝 Partners & Integrations
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### Open Integrations
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- Ollama (local LLM)
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- OpenAI API
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- DeepSeek API
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- Telegram Bot API
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- Discord Webhooks
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### Planned Integrations
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- Dify (LLM backend)
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- MCP (Model Context Protocol)
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- Anthropic Claude
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- Hugging Face models
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- Web3 wallets (for DAO auth)
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---
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## 📊 Metrics & Transparency
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### Public Metrics (Planned)
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- GitHub stars/forks
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- Active contributors
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- Issue resolution time
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- Release cadence
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- Community size (Discord)
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### Development Transparency
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- Public roadmap (GitHub Projects)
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- Open issue tracker
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- Public discussions
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- Regular community calls (planned)
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---
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## 💬 Community
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- **GitHub**: https://github.com/daarion/dagi-stack
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- **Discord**: https://discord.gg/daarion
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- **Discussions**: https://github.com/daarion/dagi-stack/discussions
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- **Email**: dev@daarion.city
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---
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## 🎉 Why Open Core?
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1. **Accelerate Innovation**: Community contributions improve core faster
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2. **Reduce Vendor Lock-in**: Users can self-host, modify, extend
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3. **Build Trust**: Transparent codebase, security audits possible
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4. **Ecosystem Growth**: More providers = more value for everyone
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5. **Sustainable Business**: Commercial extensions fund ongoing development
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---
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**DAGI Stack is infrastructure, not a product.** By open-sourcing the core, we enable the entire DAARION ecosystem to build on a shared foundation while maintaining flexibility for specialized/commercial use cases.
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---
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**Version**: 0.2.0
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**License**: MIT (core)
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**Last Updated**: 2024-11-15
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