edge-router

Solid

Route AI agent compute tasks to the cheapest viable backend. Supports local inference (Ollama), cloud GPU (Vast.ai), and quantum hardware (Wukong 72Q). Use when an agent needs to decide where to run a task, optimize compute costs, check backend availability, or execute workloads across edge/cloud/quantum infrastructure.

DevOps & Infrastructure 3,964 stars 1088 forks Updated 1 months ago MIT

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Quality Score: 86/100

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Skill Content

# Edge Router Routes tasks to cheapest available backend: local (free) → cloud GPU ($0.01) → quantum ($0.10). ## API Base: `https://edge-router.gpupulse.dev/api/v1` (or localhost:3825) ### Route (recommend) ```bash curl -X POST "$BASE/route" -H "Content-Type: application/json" \ -d '{"task_type": "inference"}' ``` ### Execute (route + run) ```bash curl -X POST "$BASE/execute" -H "Content-Type: application/json" \ -d '{"task_type": "inference", "payload": {"model": "llama3.2:1b", "prompt": "hello"}}' ``` ### Task Types - `inference` → local first, cloud fallback - `training` → cloud GPU - `quantum` → Wukong 72Q - `auto` → cheapest available ### Other - `GET /backends` — list + status - `GET /stats` — routing statistics - `GET /health` — health check

Details

Author
openclaw
Repository
openclaw/skills
Created
4 months ago
Last Updated
1 months ago
Language
Python
License
MIT

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