codex-balancer

I wrote this README by hand, no LLM :)

Balancing usage across several ChatGPT Codex accounts.

Install

go install github.com/supabitapp/codex-balancer@latest

Running the proxy

codex-balancer server           # serve the proxy with a TUI at

The server runs at http://127.0.0.1:8317

• /v1/responses — HTTP POST (SSE or JSON) and WebSocket GET
• /codex/responses and /v1/codex/responses — equivalent HTTP POST and WebSocket GET aliases for pi
• /v1/alpha/search, /v1/images/generations and /v1/images/edits — unary POST proxies for Codex's standalone web search and image tools, sent with a pool account's credentials
• /dashboard — HTML dashboard
• /stats — JSON stats of the server
• /accounts — add an account. On a real server, send this to your friends so they join the pool without exposing credentials.

The TUI also allows you to put a pause or priority on some accounts.

CLI

There is a CLI to manage the accounts

codex-balancer accounts add                 # sign in through a local browser
codex-balancer accounts list
codex-balancer accounts mode you@example.com priority
codex-balancer accounts mode you@example.com normal

Adding an account preserves its existing model training setting. Self-serve Business Pro Lite (self_serve_business_prolite) accounts route using their per-account quota. Other Business and Enterprise workspaces are displayed but excluded from routing.

Use the CLI to manage client API keys:

codex-balancer keys add my-laptop
codex-balancer keys list
codex-balancer keys rm my-laptop

keys list includes the input, cached, output, and total tokens attributed to each key.

State lives in ~/.codex-balancer/state.db.

Point Codex at it

On each machine that runs Codex, export a key from the server before starting Codex:

export CODEX_BALANCER_API_KEY="<server-key>"

add that to your ~/.zshrc or whatever env loading mechanism or shell you use.

Then in ~/.codex/config.toml:

model_provider = "balancer"

[model_providers.balancer]
name = "OpenAI" # must be exactly this for server-side compaction to work
base_url = "http://127.0.0.1:8317/v1"
env_key = "CODEX_BALANCER_API_KEY"
requires_openai_auth = true
supports_websockets = true

Point pi at it

export CODEX_BALANCER_API_KEY="<server-key>"

Merge this into ~/.pi/agent/models.json, keeping any unrelated providers:

{
  "providers": {
    "openai-codex": {
      "baseUrl": "http://127.0.0.1:8317/v1",
      "apiKey": "$CODEX_BALANCER_API_KEY"
    }
  }
}

Observability

HTTP Responses has verbose, request-correlated logs. Use server -no-tui -json for JSON logs; clients can report X-Codex-Balancer-Request-Id from response headers. Add -otel to export real traces to a configured OTLP HTTP collector:

OTEL_EXPORTER_OTLP_ENDPOINT=http://127.0.0.1:4318 codex-balancer server -no-tui -json -otel

See OBSERVABILITY.md for trace configuration, privacy/buffering limits, and how to check account-switch boundaries and actual cached-token usage. Tracing is optional and does not change routing or retry behavior.

Routing

Routing logic is in ROUTING.md.