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OpenClaw Integration
Once the Tightwad cluster or speculative proxy is running, register it as a provider in OpenClaw so agents can use the models.
Add to ~/.openclaw/openclaw.json under providers:
"tightwad": {
"baseUrl": "http://<rocm-machine-ip>:8080/v1",
"apiKey": "no-key",
"api": "openai-completions"
}For the speculative decoding proxy:
"tightwad-proxy": {
"baseUrl": "http://127.0.0.1:8088/v1",
"apiKey": "no-key",
"api": "openai-completions"
}Add models under models (or agents.defaults.models):
"tightwad/qwen3-32b": {
"id": "qwen3-32b",
"name": "Qwen3 32B (Tightwad Cluster)",
"provider": "tightwad"
}For the proxy (output quality = target model):
"tightwad-proxy/qwen3-32b": {
"id": "qwen3-32b",
"name": "Qwen3 32B (Speculative Proxy)",
"provider": "tightwad-proxy"
}Override specific cron jobs or agents to use Tightwad models:
{
"model": "tightwad/qwen3-32b"
}Since Tightwad serves an OpenAI-compatible API, it works the same as any other provider in OpenClaw. No special configuration needed beyond the provider/model registration.
Tightwad runs alongside existing providers:
-
llama-desktop(GLM-4.7-Flash on port 8080 of Windows desktop) — may need to change ports if both run simultaneously -
ollamaproviders — unaffected, different ports -
anthropic/anthropic-fleet— cloud providers, no conflict
Port conflict note: The Windows desktop currently runs llama-server on port 8080 for GLM. If Tightwad's coordinator also uses 8080 (on the ROCm machine), there's no conflict since they're different machines. But the Windows rpc-server instances share the desktop's GPUs — running both GLM llama-server and rpc-server simultaneously may cause GPU memory pressure.
If you swap models with tightwad swap deepseek-r1-70b, the API endpoint stays the same but serves a different model. OpenClaw agents calling tightwad/qwen3-32b would get DeepSeek responses. To handle this cleanly, register each model as a separate OpenClaw model and only start the one you need, or implement a routing layer.