3cacf67cf5
- 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.
180 lines
4.9 KiB
Markdown
180 lines
4.9 KiB
Markdown
# Changelog
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All notable changes to DAGI Stack will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [Unreleased]
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### Planned
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- Real CrewAI integration with live agents
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- Production RBAC with PostgreSQL/MongoDB backend
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- Docker containerization for all services
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- Kubernetes deployment manifests
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- Monitoring with Prometheus + Grafana
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- CI/CD pipelines (GitHub Actions)
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- Multi-node Router federation
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---
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## [0.2.0] - 2025-11-15
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### Phase 2: Orchestration Layer - COMPLETE ✅
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#### Added
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- **Bot Gateway Service** (321 lines)
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- Telegram webhook handler
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- Discord webhook handler
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- Automatic DAO mapping
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- Router client integration
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- **microDAO RBAC Service** (212 lines)
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- Role management (admin, member, contributor, guest)
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- Entitlements resolution (10 distinct permissions)
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- User-to-DAO mapping
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- RBAC resolution API
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- **RBAC Integration in Router**
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- `rbac_client.py` for RBAC service communication
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- Automatic RBAC context injection for `mode=chat`
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- Context enrichment in `RouterApp.handle()`
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- **Chat Mode Routing**
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- New routing rule `microdao_chat` (priority 10)
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- Automatic routing for chat requests
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- RBAC-aware LLM calls
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#### Tests
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- `test-gateway.sh` - Gateway + RBAC integration (6/7 passed - 86%)
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- End-to-end flow: Bot → Gateway → Router → RBAC → LLM
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#### Known Issues
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- LLM timeout on high load (performance tuning needed, not architecture issue)
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---
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## [0.1.5] - 2025-11-15
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### CrewAI Orchestrator Integration - COMPLETE ✅
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#### Added
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- **CrewAIProvider** (122 lines)
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- HTTP-based workflow orchestration
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- Metadata enrichment
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- Error handling
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- **CrewAI Backend MVP** (236 lines)
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- 4 predefined multi-agent workflows:
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* `microdao_onboarding` - 3 agents (welcomer, role_assigner, guide)
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* `code_review` - 3 agents (reviewer, security_checker, performance_analyzer)
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* `proposal_review` - 3 agents (legal_checker, financial_analyzer, impact_assessor)
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* `task_decomposition` - 3 agents (planner, estimator, dependency_analyzer)
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- Simulated agent execution with logs
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- Workflow registry and validation
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- **Orchestrator Provider Type**
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- New `orchestrator_providers` section in config
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- Auto-registration in provider registry
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- `mode=crew` routing rule
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#### Tests
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- `test-crewai.sh` - Full CrewAI integration (13/13 passed - 100%)
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#### Configuration
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- Updated `router-config.yml` to v0.5.0
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- Added `microdao_orchestrator` agent
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---
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## [0.1.0] - 2025-11-15
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### DevTools Integration - COMPLETE ✅
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#### Added
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- **DevToolsProvider** (132 lines)
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- HTTP backend communication
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- Tool mapping (fs_read, fs_write, run_tests, notebook_execute)
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- Request enrichment with DAO context
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- **DevTools Backend MVP** (261 lines)
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- File system operations (read/write)
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- Test execution (pytest integration)
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- Notebook execution (simulated)
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- Basic security validation
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- **Provider Registry Updates**
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- Auto-detect DevTools agents from config
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- Dynamic provider instantiation
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#### Tests
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- `test-devtools.sh` - E2E DevTools flow (10/11 passed - 91%)
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#### Configuration
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- Updated `router-config.yml` to v0.4.0
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- Added `devtools_tool_execution` routing rule (priority 3)
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---
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## [0.0.5] - 2025-11-15
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### Phase 1: Foundation - COMPLETE ✅
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#### Added
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- **Config Loader** (195 lines)
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- PyYAML + Pydantic validation
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- 8 Pydantic models for config schema
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- Config path resolution with env var support
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- Helper functions for config access
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- **Provider Registry** (67 lines initially)
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- Config-driven provider builder
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- LLM provider support (OpenAI, Ollama)
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- **Routing Engine** (156 lines)
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- Priority-based rule matching
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- Complex conditions (AND, metadata, API key checks)
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- RoutingTable class
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- **RouterApp** (152 lines)
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- Main orchestration class
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- `from_config_file()` factory
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- `async handle()` method
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- Provider info and routing info methods
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- **FastAPI HTTP Layer** (171 lines)
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- POST /route - main routing endpoint
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- GET /health, /info, /providers, /routing
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- Swagger/OpenAPI docs
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- Error handling
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#### Tests
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- `test_config_loader.py` - Unit tests (7/7 passed)
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#### Configuration
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- Initial `router-config.yml` with 2 LLM profiles
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- DevTools agent definition
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- 4 routing rules
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---
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## [0.0.1] - 2025-11-14
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### Initial Setup
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#### Added
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- Project structure
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- Basic FastAPI skeleton
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- Environment setup
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- Ollama + qwen3:8b integration
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- `.env` configuration
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---
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[Unreleased]: https://github.com/daarion/dagi-stack/compare/v0.2.0...HEAD
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[0.2.0]: https://github.com/daarion/dagi-stack/compare/v0.1.5...v0.2.0
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[0.1.5]: https://github.com/daarion/dagi-stack/compare/v0.1.0...v0.1.5
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[0.1.0]: https://github.com/daarion/dagi-stack/compare/v0.0.5...v0.1.0
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[0.0.5]: https://github.com/daarion/dagi-stack/compare/v0.0.1...v0.0.5
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[0.0.1]: https://github.com/daarion/dagi-stack/releases/tag/v0.0.1
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