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What you can do with Antirion

Antirion is an open-source AI gateway written in Rust, shipped as one binary with a built-in web console, that routes, secures, budgets and observes LLM calls across many model providers.

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eliasbiondo/antirion on GitHub

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What do you want to do?

5 use cases

  • Send every app's LLM calls through one endpoint

    Run one gateway that forwards OpenAI-style requests to your provider keys.

    View prompt
    Using the eliasbiondo/antirion README, configure the OpenAI SDK in <project path> to use base URL http://localhost:8080/v1 and the gateway key in ANTIRION_API_KEY, then send a chat request with model chat. Expected output: a chat completion JSON response. Verify that the request appears in the Request log in the console.

  • Cap LLM spend per team, project or key

    Set dollar or token budgets and get alerts before a budget runs out.

    View prompt
    Using the eliasbiondo/antirion README, create one gateway key per project and set a dollar budget on each key in the console. Expected output: a list of keys with their budgets. Verify that a test request from one key shows its cost in the cost ledger.

  • Find out why an LLM call failed or cost too much

    Read the route, status, tokens and cost of any request in the request log.

    View prompt
    Using the eliasbiondo/antirion README, find the request in the Request log that matches <request description> and report its status, Model, key, tokens, latency and cost. Expected output: a short summary of that request. Verify that the reported values match the request details in the console.

  • Screen prompts for PII and prompt injection

    Add guardrails that check requests, responses and streams before models see them.

    View prompt
    Using the eliasbiondo/antirion README, enable the PII guardrail for the key <key name> in the console and send a test request containing a fake email address. Expected output: the request is redacted or blocked as configured. Verify the result in the Request log.

  • Rerun the gateway benchmark on your own AWS account

    Use the bench harness to measure Antirion overhead against your own setup.

    View prompt
    Using the eliasbiondo/antirion README and docs/benchmarks.md, prepare the bench/ harness for <AWS region> following the reproduction steps. Expected output: a results summary with overhead p50 and p99 and error rate. Verify that the load generator and upstream run on separate machines as the method requires.

How to use Antirion

  1. Check you have what it needs: Docker installed on the machine that will run the gateway; An API key from OpenAI or Anthropic; A web browser to open the console at http://localhost:8081/ui/.
  2. Open eliasbiondo/antirion on GitHub and read the README and license.
  3. Run docker run -p 8080:8080 -p 8081:8081 -v antirion-data:/var/lib/antirion eliasbiondo/antirion and copy the admin token printed on the first start.
  4. In the console at http://localhost:8081/ui/, open Providers, choose Add provider, paste your API key, run Test, then Add provider.
  5. Open Models, choose Add model, pick a model from the provider's list, name it chat, and click Add model.
  6. Open API keys, choose Create key, name it for your app, and copy the key, which is shown only once.

These steps come from our top use case, Send every app's LLM calls through one endpoint, which also has a copy-paste agent prompt.

Antirion alternatives · Best AI repos for Software and DevOps

About this repo

  • Who it is forBuilt for developers and platform teams who run apps that call several LLM providers and want one endpoint, spend limits and request visibility.
  • Why it is hot
  • LanguageRust
  • Sourcegithub.com/eliasbiondo/antirion · Back to Hot repos

Requirements

  • Docker installed on the machine that will run the gateway
  • An API key from OpenAI or Anthropic
  • A web browser to open the console at http://localhost:8081/ui/
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Questions about Antirion

What is Antirion?

Antirion is an open-source AI gateway written in Rust, shipped as one binary with a built-in web console, that routes, secures, budgets and observes LLM calls across many model providers. It is an open-source project on GitHub: https://github.com/eliasbiondo/antirion.

Who is Antirion for?

Built for developers and platform teams who run apps that call several LLM providers and want one endpoint, spend limits and request visibility.

What can I do with Antirion?

5 use cases so far, for example: Send every app's LLM calls through one endpoint; Cap LLM spend per team, project or key; Find out why an LLM call failed or cost too much. Each has steps and a copy-paste agent prompt.

What do I need to run Antirion?

Docker installed on the machine that will run the gateway; An API key from OpenAI or Anthropic; A web browser to open the console at http://localhost:8081/ui/.

What are alternatives to Antirion?

Other hot AI repos in Software and DevOps: Harness2, iFixAi, Orca, Diagram Design, AI Memory.

Is Antirion safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.