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Axonhub

AxonHub is an open-source, Go-based AI gateway that routes requests from AI SDKs to multiple LLM providers, with failover, load balancing, cost management and request tracing.

Independent OpenViST project profile, based on linked sources.

Axonhub — OpenViST project profile in AI Infrastructure & Serving.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use AxonHub when an application needs a shared gateway between its SDK and multiple LLM providers, or when provider routing, failover, tracing or cost tracking are part of the operational workflow.

Who it is for

  • Developers building applications that call large language models.
  • Teams that want to route requests from existing AI SDKs across multiple model providers.
  • Operators seeking gateway-level controls for routing, tracing and usage costs.

Documented uses

  • Route requests from an existing SDK to different LLM providers through a gateway.
  • Configure failover or load balancing across model channels.
  • Inspect request traces to investigate model calls.
  • Track request-level usage costs.
Before you choose

Requirements & limits

The public repository describes AxonHub as open source and is licensed under Apache-2.0. Docker and self-hosted server platforms are listed.

  • AxonHub is infrastructure to operate between an application and model providers, rather than an end-user assistant or a model provider.
  • The project identifies OpenAI and Anthropic SDKs and Claude, Gemini and DeepSeek among the relevant ecosystems.
  • Its described operational functions include failover, load balancing, end-to-end tracing and cost control.
  • The repository is Go-based and lists Docker and self-hosting as platforms.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up AxonHub with a provider and client API key

Initialize AxonHub, configure an AI provider channel, and create a key for clients.

Before you start

  • A deployed AxonHub instance and its access address.
  • An AI provider API key.

Steps

  1. Open the AxonHub access address and follow the initialization wizard to create an administrator account.

  2. In Channels, add an AI provider and its API key; configure supported models, test the connection, and enable the channel.

  3. In API Keys, create an AxonHub API key for client use.

Expected outcome

AxonHub is initialized with an enabled provider channel and a client API key, ready for a client request.

Guide limitations

  • The setup instructions assume deployment is already complete; deployment steps are not included here.
  • Provider choice and model availability are not specified.
Source-based practical guide

Send a chat-completion request through AxonHub with the OpenAI Python SDK

Use the OpenAI Python SDK to send a chat-completion request to AxonHub.

Before you start

  • A running AxonHub instance accessible at the configured base URL.
  • An AxonHub API key.
  • A configured provider channel and supported model.
  • The OpenAI Python SDK.

Steps

  1. Create an OpenAI client with base_url="http://localhost:8090/v1" and your AxonHub API key.

  2. Call client.chat.completions.create with model gpt-4o and a user message such as Hello, AxonHub!.

  3. Read the response text from response.choices[0].message.content.

Expected outcome

The example reads the returned chat-completion message content.

Guide limitations

  • The example uses a local base URL and a placeholder key; adjust them for the AxonHub instance in use.
  • Successful execution depends on the configured channel supporting the requested model.
Evidence and transparency

Sources & review

Source record details
Source availability
Active
Sources checked
7 October 2026
Original website title
looplj/axonhub · Official homepage title · retained in its source language