looplj/axonhub

⚡️ Open-source AI Gateway — Use any SDK to call 100+ LLMs. Built-in failover, load balancing, cost control & end-to-end tracing.

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Summary Information

Updated 8 minutes ago
Added to GitGenius on September 13th, 2026
Created on September 9th, 2025
Open Issues & Pull Requests: 105 (+0)
GitHub issues: Enabled
Number of forks: 700
Total Stargazers: 5,215 (+1)
Total Subscribers: 14 (+0)

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Issue Activity (beta)

Open issues: 72
New in 7 days: 16
Closed in 7 days: 24
Avg open age: 78 days
Stale 30+ days: 47
Stale 90+ days: 20

Recent activity

Opened in 7 days: 14
Closed in 7 days: 18
Comments in 7 days: 3
Events in 7 days: 11

Top labels

  • enhancement (241)
  • bug (234)
  • question (109)
  • stale (71)
  • faq (18)
  • wait for info (13)
  • invalid (12)
  • unplanned (7)

Detailed Description

AxonHub is an open-source AI gateway that enables developers to call over 100 large language models using any SDK without modifying application code.

The tool solves the problem of managing multiple LLM providers and their varying APIs by acting as a unified interface. It abstracts away provider-specific differences, allowing applications built with any SDK to transparently route requests to different models. The gateway includes built-in failover mechanisms to handle provider outages, load balancing to distribute requests across multiple providers or models, cost control features to manage spending, and end-to-end tracing for observability and debugging.

Developers should adopt this tool if they need to work with multiple LLM providers or want flexibility to switch between models without rewriting application code. It suits projects that require high availability, cost optimization across different model providers, or the ability to experiment with different LLMs in production. The tool is particularly valuable for teams building agent systems or applications that benefit from model diversity and automatic failover capabilities.

The project shows active development with regular updates and improvements. The codebase is maintained in Go, providing performance suitable for a gateway workload. The project maintains documentation in multiple languages and has established partnerships with API providers, indicating ongoing investment in the ecosystem around the tool.