Map

GoModel

Toolbox toolboxgolangai-gatewayllmproxyobservabilityGoMIT ↳ show in map Markdown
title
GoModel
type
toolbox
summary
Go-based AI gateway with OpenAI-compatible unified API across 10+ LLM providers
tags
golang, ai-gateway, llm, proxy, observability
repo
https://github.com/ENTERPILOT/GoModel
language
Go
license
MIT
created
2026-04-22
updated
2026-04-22

GoModel is a Go-based AI gateway that exposes a single OpenAI-compatible API over 10+ LLM providers: OpenAI, Anthropic, Google Gemini, Groq, OpenRouter, Z.ai, xAI (Grok), Azure OpenAI, Oracle Generative AI, and Ollama. It's explicitly positioned as a LiteLLM alternative — same problem space (unified LLM access layer for app developers), different language (Go vs Python).

Built by the ENTERPILOT team, MIT-licensed, 379 stars, created December 2025.

What it covers

The gateway auto-detects which providers are available from the credentials you supply. The feature grid from the README:

Feature Scope
Chat completions All 10 providers
/v1/responses (OpenAI Responses API) All 10 providers
Embeddings 7 providers (not Anthropic, Oracle, Ollama-partial)
Files 5 providers (OpenAI, Gemini, Groq, OpenRouter, xAI, Azure)
Batches 6 providers
Provider-native passthrough at /p/{provider}/... OpenAI, Anthropic, OpenRouter, Z.ai by default

Plus: usage analytics by model/day/period, audit logging, response caching, Prometheus metrics, admin dashboard, Swagger UI, guardrails pipeline, configurable storage (SQLite, PostgreSQL, MongoDB).

Operational posture

Designed as a production-ready deployable, not a library:

  • Docker image at enterpilot/gomodel on Docker Hub.
  • Docker Compose profiles for infrastructure-only (Redis/Postgres/MongoDB/Adminer) or full-stack (+ GoModel + Prometheus).
  • GOMODEL_MASTER_KEY environment variable as the API auth gate. The README specifically warns that without this key all endpoints are unauthenticated.
  • Credentials passed via environment variables; README recommends --env-file over -e to avoid leaking secrets through shell history and process lists.

Go 1.26.2+ required when building from source.

Why it matters

LiteLLM's Python posture has always been awkward for teams running a Go or Rust backend — adding a Python process just for the gateway is operationally expensive. GoModel removes that impedance mismatch: single binary, single runtime, fits into a Go deployment exactly like any other service.

Beyond that, the passthrough feature (/p/{provider}/...) is the interesting structural choice. Instead of forcing every client to route through an OpenAI-schema shim, it exposes the raw provider API with just auth/logging/metering in the middle. That matches how production traffic actually splits: some paths want normalized OpenAI-shape, some want provider-native features that don't fit in the OpenAI schema (Anthropic's prompt caching, Gemini's grounding, etc.).

Repo

https://github.com/ENTERPILOT/GoModel — 379 stars, MIT. Docs at gomodel.enterpilot.io. Discord and Docker Hub linked from the README.

  • rawquery — adjacent tool operating on structured data (CLI-first data platform), not LLM gateway
  • build-your-own-openclaw — agent-building tutorial; would pair with GoModel if you wanted to deploy the agent behind a gateway
Linked from