Connect an app

2026-08-31

Tempo9 speaks the protocols your tools already speak. In most cases connecting one is a change of address, not a change of code — and if you have already pulled models with Ollama, there is nothing to download either.

Start the server

tempo9 --gguf ~/models/qwen3-8b-q4ks.gguf

It listens on http://127.0.0.1:11435, loopback only — the wildcard is never bound, so nothing off this machine can reach it. Change the port with --port.

Your app has a "custom OpenAI endpoint" field

Most local-AI apps do. Fill it in:

No key is required and none is checked, which is safe here only because the server is loopback-bound. Do not put it behind a tunnel or a reverse proxy and leave it that way.

Apps in this category include Cherry Studio, AnythingLLM, and anything else built on an OpenAI client — we have not tested each one, so treat this as "the field exists and this is what goes in it" rather than a certification.

Your app only knows how to talk to Ollama

Some apps do not offer a generic endpoint field at all; they have an Ollama integration and nothing else. Those work too. Point them at:

http://127.0.0.1:11435

Tempo9 serves Ollama's native routes alongside its own: /api/tags, /api/chat, /api/generate, /api/show, /api/version, /api/ps. Streaming is newline-delimited JSON and tool-call arguments are objects, exactly as those clients expect.

You already downloaded models with Ollama

Full detail, including what is never written: Ollama models.

Then you do not need to download them again. Ollama stores each model as a plain GGUF file, which is what Tempo9 loads, so it can read them where they sit:

tempo9 --list-ollama

qwen3:8b            4.68 GiB  /Users/you/.ollama/models/blobs/sha256-1f3d...
llama3.2:latest     1.88 GiB  /Users/you/.ollama/models/blobs/sha256-a41c...

tempo9 --ollama qwen3:8b

This is read-only. Nothing is copied, converted, moved, or written into Ollama's store — your models stay exactly as Ollama left them, and Ollama keeps working. If you moved the store, OLLAMA_MODELS is respected.

A bare name means :latest, the same as ollama run.

Agent tools

Claude Code, Codex and similar clients do not use the OpenAI chat protocol — they each want their own. Tempo9 serves all three from one process:

Agent workloads are the case Tempo9 is built for: many requests at once, long and growing context, heavy tool calling. That is where the architecture shows up rather than in a single stream — see the benchmarks.

What it does not do

Also: Limits.

Worth knowing before you wire something up:

• No embeddings. /api/embed and /v1/embeddings are not served; the Ollama route answers 501 and says so rather than pretending.
• One model per process. /v1/models and /api/tags report the one that is loaded. Run a second server on another port for a second model.
• Vision needs a tower. Image input works with --tower <dir>. A GGUF vision projector inside an Ollama model is detected but not loaded; the server tells you when it sees one.
• No authentication. By design, and only defensible because it is loopback-bound.