Feature request: openai_compatible API_TYPE so any OpenAI-compatible endpoint works with no service class

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Valutazione

Difficoltà
3/5
Tempo stimato
1-2 giorni
Idoneità per principianti
58/100
Tipo di issue
Funzionalità
Chiarezza
Abbastanza chiara
Stato di attività
Attiva
Stack tecnologico
python
Ambito
backend

Direzione di ricerca

Start by reading the custom-model path in the agents.yaml config and the model factory where service classes are registered (ufo/config and ufo/llm or similar module). Trace how API_BASE, API_KEY, and API_MODEL flow into an existing OpenAI-style service class, then add an openai_compatible API_TYPE that reuses it with no code required. Done means HOST_AGENT and APP_AGENT can point at any OpenAI-compatible endpoint purely via config.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Hi — I run DemonRoute (demonroute.com), an OpenAI-compatible API at https://api.demonroute.com/v1.

I will be direct about why I am here: we are talking to a lot of projects, because there is no large established provider for no-subscription, anonymous API keys for open-weight uncensored models. We are earning distribution one repo at a time.

UFO is a case where the current path is close but not quite open. Today the custom-model route in agents.yaml takes API_BASE, API_KEY, and API_MODEL, but using it still means writing a Python service class and registering it in the model factory. That is a real barrier for anyone who just wants to point HOST_AGENT or APP_AGENT at an OpenAI-compatible endpoint.

The feature ask: add an openai_compatible API_TYPE that sends standard chat-completions requests to API_BASE with API_KEY and API_MODEL, no code required. That would make any OpenAI-compatible provider work out of the box, DemonRoute included.

Why it matters for UFO users: every desktop step is an LLM call with screenshots attached, so cost adds up fast, and your own docs flag cost optimization. We carry Dolphin, MythoMax, Hermes, and abliterated Llama/Qwen builds that handle adversarial automation tasks without refusing, and we never train on user content. Nothing on a user's screen is ever used to train a model.

Who is behind it: during the NFT peak I became the largest NFT artist on the third-largest chain in the world, overnight, with zero funding. That turned into consulting for Fortune 500s, celebrities, and emerging tech companies. I run everything under NFT Demon Holdings LLC, and DemonRoute is my passion priority.

Reciprocal: any app that lists DemonRoute as a provider option gets listed on demonroute.com/integrations.

Jeremy, DemonRoute

Lingua principale
Python
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