Apple
|
0c8bef82f4
|
feat: Add Alateya, Clan, Eonarch agents + fix gateway-router connection
## Agents Added
- Alateya: R&D, biotech, innovations
- Clan (Spirit): Community spirit agent
- Eonarch: Consciousness evolution agent
## Changes
- docker-compose.node1.yml: Added tokens for all 3 new agents
- gateway-bot/http_api.py: Added configs and webhook endpoints
- gateway-bot/clan_prompt.txt: New prompt file
- gateway-bot/eonarch_prompt.txt: New prompt file
## Fixes
- Fixed ROUTER_URL from :9102 to :8000 (internal container port)
- All 9 Telegram agents now working
## Documentation
- Created PROJECT-MASTER-INDEX.md - single entry point
- Added various status documents and scripts
Tokens configured:
- Helion, NUTRA, Agromatrix (existing)
- Alateya, Clan, Eonarch (new)
- Druid, GreenFood, DAARWIZZ (configured)
|
2026-01-28 06:40:34 -08:00 |
|
Apple
|
7b91c8e83c
|
feat(foundation): FOUNDATION_UPDATE implementation
## Documentation (20 files)
- DAARION Ontology Core v1 (Agent → MicroDAO → Node → District)
- User Onboarding & Identity Layer (DAIS)
- Data Model UPDATE, Event Catalog, Governance & Permissions
- Rooms Layer, City/MicroDAO/Agents/Nodes Interface Architecture
- Helper files: ontology-summary, lifecycles, event-schemas
## Database Migration (027)
- DAIS tables: dais_identities, dais_emails, dais_wallets, dais_keys
- agent_assignments table for Assignment Layer
- rooms table for Rooms Layer
- event_outbox for NATS event delivery
- New enums: agent_role, microdao_type, node_kind, node_status, etc.
- Updated agents, microdaos, nodes tables with ontology fields
## Backend
- DAIS service & routes (/api/v1/dais/*)
- Assignment service & routes (/api/v1/assignments/*)
- Domain types for DAIS and Ontology
## Frontend
- Ontology types (Agent, MicroDAO, Node, DAIS, Assignments)
- API clients for DAIS and Assignments
- UI components: DaisProfileCard, AssignmentsPanel, OntologyBadge
Non-breaking update - all existing functionality preserved.
|
2025-11-29 15:24:38 -08:00 |
|
Apple
|
4601c6fca8
|
feat: add Vision Encoder service + Vision RAG implementation
- Vision Encoder Service (OpenCLIP ViT-L/14, GPU-accelerated)
- FastAPI app with text/image embedding endpoints (768-dim)
- Docker support with NVIDIA GPU runtime
- Port 8001, health checks, model info API
- Qdrant Vector Database integration
- Port 6333/6334 (HTTP/gRPC)
- Image embeddings storage (768-dim, Cosine distance)
- Auto collection creation
- Vision RAG implementation
- VisionEncoderClient (Python client for API)
- Image Search module (text-to-image, image-to-image)
- Vision RAG routing in DAGI Router (mode: image_search)
- VisionEncoderProvider integration
- Documentation (5000+ lines)
- SYSTEM-INVENTORY.md - Complete system inventory
- VISION-ENCODER-STATUS.md - Service status
- VISION-RAG-IMPLEMENTATION.md - Implementation details
- vision_encoder_deployment_task.md - Deployment checklist
- services/vision-encoder/README.md - Deployment guide
- Updated WARP.md, INFRASTRUCTURE.md, Jupyter Notebook
- Testing
- test-vision-encoder.sh - Smoke tests (6 tests)
- Unit tests for client, image search, routing
- Services: 17 total (added Vision Encoder + Qdrant)
- AI Models: 3 (qwen3:8b, OpenCLIP ViT-L/14, BAAI/bge-m3)
- GPU Services: 2 (Vision Encoder, Ollama)
- VRAM Usage: ~10 GB (concurrent)
Status: Production Ready ✅
|
2025-11-17 05:24:36 -08:00 |
|