Rename "OpenGradient Local" to "OpenGradient Veil" and add models command

README.md

@@ -61,8 +61,8 @@ That's it. Every response is verified before you see it — check the
 on the body). Streaming works too; it's verified before the first token replays.
 
 Useful commands: `og-veil test` (send a one-off prompt to check the path),
-`og-veil stop`, `og-veil status`, `og-veil endpoint` (re-prints the env vars),
-`og-veil update`, `og-veil logout`.
+`og-veil stop`, `og-veil status`, `og-veil env` (re-prints the env vars),
+`og-veil models` (list available models), `og-veil update`, `og-veil logout`.
 
 ### Use it with Hermes Agent
 

tests/test_cli.py

@@ -1,4 +1,4 @@
-"""CLI wiring: first-run login, session reuse, background-by-default, endpoint, update."""
+"""CLI wiring: first-run login, session reuse, background-by-default, env, models, update."""
 
 from __future__ import annotations
 
@@ -58,13 +58,23 @@ def test_setup_with_yes_starts_background():
     assert result.exit_code == 0
 
 
-def test_endpoint_prints_env_vars():
+def test_env_prints_env_vars():
     with mock.patch("veil.daemon.running_pid", return_value=4321):
-        result = CliRunner().invoke(cli.main, ["endpoint"])
+        result = CliRunner().invoke(cli.main, ["env"])
     assert "OPENAI_BASE_URL=http://127.0.0.1:11434/v1" in result.output
     assert result.exit_code == 0
 
 
+def test_models_lists_known_models():
+    result = CliRunner().invoke(cli.main, ["models"])
+    assert result.exit_code == 0
+    # Should print at least one model name derived from the SDK's TEE_LLM enum.
+    from opengradient import TEE_LLM
+
+    sample = next(iter(TEE_LLM)).value.split("/", 1)[1]
+    assert sample in result.output
+
+
 def test_test_command_posts_prompt_to_localhost_and_prints_reply():
     resp = mock.MagicMock(
         status_code=200,

veil/__init__.py

@@ -1,4 +1,4 @@
-"""OpenGradient Local — self-verifying private-inference proxy for AI agents.
+"""OpenGradient Veil — self-verifying private-inference proxy for AI agents.
 
 Point any OpenAI-compatible SDK at this process (one env var) and prompts are
 routed through OpenGradient's decentralized network of attestable AWS Nitro TEE

veil/cli.py

@@ -2,8 +2,8 @@
 
 The common path is a single command: run ``og-veil`` and it logs you in on first
 use, then starts the local server in the background. Individual steps (``serve``,
-``login``, ``stop``, ``status``, ``endpoint``, ``test``, ``update``, ``logout``)
-are available on their own too.
+``login``, ``stop``, ``status``, ``env``, ``models``, ``test``, ``update``,
+``logout``) are available on their own too.
 """
 
 from __future__ import annotations
@@ -21,7 +21,7 @@
 @click.option("-v", "--verbose", is_flag=True, help="Enable debug logging.")
 @click.pass_context
 def main(ctx: click.Context, verbose: bool) -> None:
-    """OpenGradient Local — drop-in, self-verifying private inference for AI agents.
+    """OpenGradient Veil — drop-in, self-verifying private inference for AI agents.
 
     Run with no command to do everything: set up on first run, then start the server.
     """
@@ -157,11 +157,11 @@ def _start_server(config: ServerConfig, *, foreground: bool) -> None:
         # Already running — surface that clearly rather than erroring out.
         existing = running_pid()
         if existing:
-            click.secho(f"OpenGradient Local is already running (pid {existing}).", fg="yellow")
+            click.secho(f"OpenGradient Veil is already running (pid {existing}).", fg="yellow")
             click.echo("  Stop it with: og-veil stop")
             return
         raise click.ClickException(str(exc))
-    click.secho(f"✓ OpenGradient Local running in the background (pid {pid}).", fg="green")
+    click.secho(f"✓ OpenGradient Veil running in the background (pid {pid}).", fg="green")
     click.echo(f"  Base URL : {config.advertised_base_url()}")
     click.echo(f"  Logs     : {log_path()}")
     click.echo("  Stop     : og-veil stop")
@@ -179,19 +179,36 @@ def stop() -> None:
         click.secho(f"✓ Stopped background server (pid {pid}).", fg="green")
 
 
-@main.command()
-def endpoint() -> None:
-    """Print the env vars to point your agent at OpenGradient Local."""
+@main.command(name="env")
+def env_cmd() -> None:
+    """Print the env vars to point your agent at OpenGradient Veil."""
     from veil.daemon import running_pid
 
     config = ServerConfig.from_env()
-    click.echo("Point your agent at OpenGradient Local (one env var change):")
+    click.echo("Point your agent at OpenGradient Veil (one env var change):")
     click.secho(f"  export OPENAI_BASE_URL={config.advertised_base_url()}", bold=True)
     click.echo("  export OPENAI_API_KEY=og-veil   # ignored; your Chat session authenticates")
     if running_pid() is None:
         click.echo("\nThe server isn't running yet — start it with `og-veil`.")
 
 
+@main.command()
+def models() -> None:
+    """List the models available through OpenGradient Veil.
+
+    Derived from the SDK's canonical ``TEE_LLM`` enum — the same source the
+    local server uses for ``GET /v1/models`` — so it stays in sync with the
+    network as models are added or retired.
+    """
+    from opengradient import TEE_LLM
+
+    # Each enum value is ``provider/model``; agents send the bare model name.
+    names = sorted(m.value.split("/", 1)[1] for m in TEE_LLM)
+    click.echo("Models available through OpenGradient Veil:")
+    for name in names:
+        click.echo(f"  {name}")
+
+
 @main.command(name="login")
 @click.option("--app-url", default=DEFAULT_APP_URL, show_default=True, help="Chat app web origin.")
 @click.option("--no-browser", is_flag=True, help="Don't open a browser; print the URL instead.")

veil/server.py

@@ -150,7 +150,7 @@ def serve(config: ServerConfig) -> None:
     app = create_app(gateway)
     tee = gateway.active_tee
     print(
-        f"OpenGradient Local listening on http://{config.host}:{config.port}\n"
+        f"OpenGradient Veil listening on http://{config.host}:{config.port}\n"
         f"  Verified TEE: {tee.tee_id if tee else '?'} ({tee.endpoint if tee else '?'})\n"
         f"  Signed in as: {session.user_email or 'unknown'}\n\n"
         f"Point your agent at it (OpenAI SDK):\n"