Show HN: Kodosumi – Open-source runtime for AI agents

3 points by Padierfind 10 hours ago

Hi Hacker News, I’m part of the team behind

Kodosumi. We built it because deploying agentic services in production was much harder than building proof-of-concepts. Many frameworks let you build agents, but when you want them to run long tasks, scale across machines, or be observed/monitored reliably, things fall apart.

Kodosumi is our answer to that. It’s an open-source runtime that uses Ray + FastAPI + Litestar to let you:

Deploy “agents” and “flows” and expose APIs easily, with minimal config (just one YAML)

Scale horizontally for bursty workloads and long-running tasks without losing stability

Monitor realtime status, logs, dashboards, etc. so you can see what’s going on under the hood

Avoid vendor lock-in (you can plug in your own LLMs, vector stores, frameworks) and deploy on cloud, on-prem, Docker, Kubernetes, etc.

We’re still early, so some parts are in active development. But if you are working with AI agents — especially ones that need to run reliably over long durations / scale up under load — we think Kodosumi could save you a lot of infra pain.

Happy to answer questions, comparisons to e.g. LangChain / Ray Serve / custom setups, criticisms, etc.