System Requirements
OtherU Core runs on a single Linux host with sufficient unified or discrete GPU memory to hold your chosen model stack.
Recommended:
- AMD Ryzen AI Max+ (Strix Halo) with 128GB unified memory, or equivalent
- Linux with ROCm (AMD GPU) or CUDA (NVIDIA GPU)
- Docker + Docker Compose
- 200GB+ storage for models
Minimum (reduced model set):
- 32GB+ GPU/unified memory
- Linux with Docker + Compose
Repository Layout
otheru-core/
├── core/coordinator/ # FastAPI orchestrator (bind-mounted into container)
│ ├── routes/openai_api.py # OpenAI-compatible API handler
│ ├── council.py # Multi-tier routing
│ ├── routing.py # needs_tools() and routing decisions
│ ├── agent_chat.py # preroute_by_pattern(), orchestrator loop
│ └── tools_impl.py # All tool implementations
├── core/config/
│ └── routing_policy.json # Routing weights, tool intent keywords
├── services/hardware_bridge/
│ └── bridge.py # JetKVM WebRTC bridge
└── infrastructure/docker/
└── docker-compose.production.yml
Models
Place GGUF models in /opt/models/ and HuggingFace models in /opt/models/vllm/.
| Role | Recommended Model | Size |
|---|---|---|
| Responder (DEFAULT) | Qwen3-Next-80B-A3B Q4_K_M | 46GB |
| Orchestrator (FAST/routing) | Nemotron-Orchestrator-8B Q6_K | 6.3GB |
| Reasoner (REASONING) | DeepSeek-R1-Distill-Qwen-14B Q4_K_M | 8.4GB |
| Coder | Any strong 32B+ code model | \~50GB |
| Vision (Fara) | microsoft/Fara-7B | 16GB |
Deployment
git clone https://git.otheru.ai/otheru/otheru-core
cd otheru-core
docker compose -f infrastructure/docker/docker-compose.production.yml up -d
Service startup order
- Core dependencies — Redis, LEANN (RAG)
- Orchestrator — Nemotron-8B (tool routing)
- Responder — 80B MoE model (primary responses)
- Reasoner — 14B R1 model (deep analysis)
- Coordinator — FastAPI gateway (depends on all agents)
- Hardware Bridge — JetKVM WebRTC bridge (requires physical JetKVM)
- GSD — Autonomous dev loop (optional)
Validation Checklist
- [ ]
curl http://127.0.0.1:8080/health→{"status":"ok"} - [ ]
curl http://127.0.0.1:8080/dependencies/health→ all services healthy - [ ]
curl http://127.0.0.1:8005/stats→frame_age< 100ms (JetKVM live) - [ ]
docker logs otheru-coordinatorshows models loaded and routing ready
OpenClaw Integration
OtherU Core exposes an OpenAI-compatible API. Connect OpenClaw as a custom provider:
- Base URL:
http://127.0.0.1:8080/v1 - API Key:
local-dev-key(or configure your own) - Models:
otheru-core,otheru-council,otheru-coder,otheru-researcher
OpenClaw handles Telegram, Signal, and WhatsApp channels out of the box.
Patching the Coordinator
Coordinator source files are bind-mounted from the host — changes take effect on restart:
# Edit on host, then:
docker restart otheru-coordinator
The hardware bridge is baked into its image. Patch it via docker cp:
docker cp services/hardware_bridge/bridge.py hardware-bridge:/app/bridge.py
docker restart hardware-bridge
WMMA Ops Build (AMD gfx1151)
# Container build (recommended)
docker compose -f docker/docker-compose.benchmark.yml build
docker compose -f docker/docker-compose.benchmark.yml run --rm benchmark bash -c \
"cd /workspace/wmma_ops && ./build_and_test.sh"
# Host build
pip install -e . --no-build-isolation
Validation gates:
- Correctness checks across representative matrix sizes
- Benchmark pass for adaptive and zerocopy kernel variants (target: 21.6 TFLOPS on gfx1151)
- Regression check against baseline PyTorch matmul