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awerouter: Smart LLM Router

Route cheap/fast tasks to Flash, hard decisions to Pro.

Transparent same-protocol proxy that routes coding-agent requests by structural signals — no keyword guessing, no LLM classifier. Speaks Anthropic Messages, OpenAI Chat Completions, and OpenAI Responses.

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Ko-fi

Transparent proxy that splits coding-agent traffic across providers by cost and capability. Same-protocol passthrough — no translation.

Install

pip install awerouter

Quick Start

# 1. Init config (creates ~/.config/awerouter/{providers,routing}.json)
awerouter init

# 2. Interactively add a profile (writes both files, references stay consistent)
awerouter add
#    or edit by hand: providers.json for keys (${ENV_VAR}), routing.json for flash/pro

# 3. Start the daemon (profile name optional when only one exists)
awerouter serve [cc-router-1]     # shorthand: awerouter cc-router-1

# 4. Point CC at it — the serve banner prints both lines below
export ANTHROPIC_BASE_URL=http://127.0.0.1:20128
# aweswitch profile env: ANTHROPIC_MODEL=auto, _HAIKU_=flash, _OPUS_=pro

Config

Two files in ~/.config/awerouter/ (override with AWEROUTER_CONFIG_DIR):

providers.json — endpoints + keys, grouped by wire protocol (redacted in config show):

{
  "anthropic": {
    "stepfun":   { "base_url": "https://api.stepfun.com/step_plan", "auth": "${STEPFUN_AUTH_TOKEN}" },
    "anthropic": { "base_url": "https://api.anthropic.com",          "auth": "${ANTHROPIC_KEY}" }
  },
  "openai-chat": {
    "stepfun": { "base_url": "https://api.stepfun.com", "auth": "${STEPFUN_AUTH_TOKEN}" }
  },
  "openai-responses": {
    "openai": { "base_url": "https://api.openai.com", "auth": "${OPENAI_API_KEY}" }
  }
}

Three protocols are supported, each with its own endpoint appended to base_url:

Protocol id Endpoint Typical client
anthropic base_url + /v1/messages Claude Code (ANTHROPIC_BASE_URL)
openai-chat base_url + /v1/chat/completions OpenAI-compatible clients; Codex with wire_api = "chat"
openai-responses base_url + /v1/responses Codex (wire_api = "responses")

base_url is the prefix before the endpoint path — for openai providers, drop the trailing /v1.

The auth header is auto-detected from base_url: anthropic.comx-api-key (bare token); everyone else → Authorization (auto-prefixes Bearer ). No auth_header field needed unless the heuristic is wrong.

routing.json — strategy, no secrets (safe to commit):

{
  "settings": {
    "backgroundModel": "flash",
    "thinkModel": "pro"
  },
  "cc-router-1": {
    "protocol": "anthropic",
    "longContextThreshold": 8000,
    "destinations": {
      "flash": "stepfun,step-3.7-flash",
      "pro":   "anthropic,claude-opus-5"
    }
  }
}

settings is optional (defaults: flash/pro). It defines the model ids CC sends for background (Haiku) and think (Opus) tiers. The main loop uses auto — routed by difficulty by L3. Set these in your aweswitch profile: ANTHROPIC_DEFAULT_HAIKU_MODEL=flash, ANTHROPIC_MODEL=auto, ANTHROPIC_DEFAULT_OPUS_MODEL=pro.

Keys reference ${ENV_VAR} syntax. Missing env vars die with a clear message at startup.

Profile-based routing: routing.json groups configs under profile ids (like aweswitch). awerouter serve <profile> starts one; with a single profile it auto-selects. protocol maps the profile to a providers.json group and decides which endpoint it serves — the serve banner prints the matching client env (ANTHROPIC_BASE_URL for Claude Code, OPENAI_BASE_URL / Codex wire_api for the openai protocols). Note: openai clients are single-model, so L2 tier labels effectively never fire for them — openai traffic routes by L1 + L3 with a flash default.

How It Routes

Three-layer first-match-wins pipeline, evaluated per request:

Layer Signal Decision
L1 Capability web_search tool in body pro (flash can't run it)
L2 Tier label model == c1/flash or c1/think flash / pro respectively
L3 Difficulty token count > threshold, or has image pro; else flash

CC's /model picker sets the tier model id (c1/flash / c1/pro / c1/think). awerouter reads it and routes accordingly — no keyword parsing, no LLM classifier.

Commands

awerouter init                        # create default config (= config init)
awerouter add                         # interactively add a profile (and new providers)
awerouter list                        # list profiles (name, protocol, flash, pro, threshold)
awerouter show [PROFILE]              # show one profile or all config (redacted)
awerouter serve [PROFILE] [--port 20128] [--host 127.0.0.1]
awerouter <PROFILE>                   # shorthand for serve PROFILE
awerouter config path | show | edit | init
awerouter log [--lines 20]
awerouter stats
awerouter calibrate

calibrate shows the message-token distribution of L3 traffic (the threshold-sensitive layer; messages only — system prompt and tools are excluded) and suggests candidate longContextThreshold values at p90/p95/p99. Run it after some real traffic, then edit routing.json.

Troubleshooting

CC shows 502 status code (no body) right after launch — a shell proxy (Clash etc.) is hijacking loopback traffic. Requests to 127.0.0.1:20128 go into the proxy, whose 127.0.0.1 is itself, so nothing is listening and the proxy returns an empty 502. serve prints a warning when it detects this; fix it by exempting loopback in your shell config:

export no_proxy=127.0.0.1,localhost NO_PROXY=127.0.0.1,localhost

Then open a new terminal and relaunch CC.

Development

git clone https://github.com/mugpeng/awerouter
cd awerouter
pip install -e ".[dev]"
pytest

See docs/CONTRIBUTING.md for architecture notes, config semantics, and the release process.

Support

If awerouter saves you money, consider supporting it:

  • ⭐ Star the repo — it helps others find it.
  • Ko-fi — buy me a coffee.
  • 💬 WeChat — scan the QR code below.

WeChat Pay

awerouter is free and open source. Sponsors keep it maintained — thank you.

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