AgentWave: policy-validated assistant suggestions for Go backends

I maintain AgentWave, an MIT-licensed Go project for adding an assistant to admin panels, CRMs, dashboards, and internal tools.

The interface is small: send a request and the current screen route, then receive one action suggestion that passes a configured policy. Your application decides whether to show or apply it.

The request flow

1. Your application's backend sends a request over a private Unix socket.
2. AgentWave creates a job and asks its Codex CLI backend for a suggestion.
3. The result must match the policy. A result outside the policy becomes a failed job.
4. Your backend retrieves the result. Any action still goes through your application's permission checks.

A browser cannot connect to the Unix socket directly. Your backend acts as the proxy and supplies the actor ID from its own user or session context.

A small policy example

This example comes from the repository's README:

{
  "actions": ["help", "navigate", "lookup"],
  "modules": ["none", "home", "contacts", "deals", "reports"],
  "routePrefix": "/admin",
  "queryActions": {
    "lookup": "contacts"
  }
}

For example, an admin panel can ask where to find a contact from /admin/contacts. The assistant can return a lookup suggestion. The host application decides how to handle it.

The HTTP interface has three routes: GET /healthz, POST /jobs, and GET /job. Job submission returns a working status; the client polls until the job is ready or failed.

What you need

The Go module has no external dependencies. The generation backend requires the Codex CLI, configured model access, and any authentication that access requires. The MIT license covers AgentWave's code; it does not provide free model access.

The repository includes local setup instructions, Docker and Compose examples, and a backend proxy example. Policy validation is one layer of the integration; keep authentication and authorization in your application.

Source code and setup instructions

Feedback on the policy format, job API, and integration examples is welcome. My other Go project, NSFW Sherlock, provides a self-hosted image moderation API.

Prepared with AI assistance from the project's public documentation.