add checkpoint deployment cli support

packages/prime/src/prime_cli/api/deployments.py

@@ -82,6 +82,16 @@ def deploy_adapter(self, adapter_id: str) -> Adapter:
                 raise APIError(f"Failed to deploy adapter: {e.response.text}")
             raise APIError(f"Failed to deploy adapter: {str(e)}")
 
+    def deploy_checkpoint(self, checkpoint_id: str) -> Adapter:
+        """Deploy a checkpoint by preparing it as an adapter for inference."""
+        try:
+            response = self.client.post(f"/rft/checkpoints/{checkpoint_id}/deploy")
+            return Adapter.model_validate(response.get("adapter"))
+        except Exception as e:
+            if hasattr(e, "response") and hasattr(e.response, "text"):
+                raise APIError(f"Failed to deploy checkpoint: {e.response.text}")
+            raise APIError(f"Failed to deploy checkpoint: {str(e)}")
+
     def unload_adapter(self, adapter_id: str) -> Adapter:
         """Unload an adapter from inference."""
         try:

packages/prime/src/prime_cli/commands/deployments.py

@@ -172,27 +172,62 @@ def list_deployments(
 def create_deployment(
     ctx: typer.Context,
     model_id: Optional[str] = typer.Argument(None, help="Model ID to deploy"),
+    checkpoint_id: Optional[str] = typer.Option(
+        None,
+        "--checkpoint-id",
+        help="Deploy a Hosted Training checkpoint by checkpoint ID",
+    ),
     yes: bool = typer.Option(False, "--yes", "-y", help="Skip confirmation prompt"),
 ) -> None:
     """Deploy a model for inference.
 
     Makes the trained model available for inference requests.
-    Model must be in READY status.
+    Model must be in READY status. To deploy a checkpoint, pass --checkpoint-id.
 
     Example:
 
         prime deployments create <model_id>
 
         prime deployments create <model_id> --yes
+
+        prime deployments create --checkpoint-id <checkpoint_id>
     """
-    if model_id is None:
+    if model_id and checkpoint_id:
+        console.print("[red]Error:[/red] Use either MODEL_ID or --checkpoint-id, not both.")
+        raise typer.Exit(1)
+
+    if model_id is None and checkpoint_id is None:
         console.print(ctx.get_help())
         raise typer.Exit(0)
 
     try:
         api_client = APIClient()
         deployments_client = DeploymentsClient(api_client)
 
+        if checkpoint_id:
+            console.print("[bold]Deploying checkpoint:[/bold]")
+            console.print(f"  Checkpoint ID: {checkpoint_id}")
+            console.print()
+
+            if not yes:
+                confirm = typer.confirm("Are you sure you want to deploy this checkpoint?")
+                if not confirm:
+                    console.print("Cancelled.")
+                    raise typer.Exit(0)
+
+            adapter = deployments_client.deploy_checkpoint(checkpoint_id)
+
+            console.print("[green]Deployment initiated successfully![/green]")
+            console.print(f"Adapter ID: [cyan]{adapter.id}[/cyan]")
+            console.print(f"Status: [yellow]{adapter.deployment_status}[/yellow]")
+            console.print("\n[dim]The model is being deployed. This may take a few minutes.[/dim]")
+            console.print("[dim]Use 'prime deployments list' to check deployment status.[/dim]")
+
+            _print_inference_usage(adapter.base_model, adapter.id)
+            return
+
+        assert model_id is not None
+
         # Get model to validate status
         model = deployments_client.get_adapter(model_id)
 

packages/prime/tests/test_deployments.py

@@ -1,12 +1,42 @@
 from types import SimpleNamespace
 from typing import Any
 
+from prime_cli.api.deployments import DeploymentsClient
+from prime_cli.client import APIError
 from prime_cli.main import app
 from prime_cli.utils import strip_ansi
 from typer.testing import CliRunner
 
 runner = CliRunner()
 
+TEST_ENV = {"PRIME_API_KEY": "dummy", "PRIME_DISABLE_VERSION_CHECK": "1", "COLUMNS": "200"}
+
+
+def _adapter_response(
+    *,
+    adapter_id: str = "adapter-123",
+    base_model: str = "meta-llama/Llama-3.1-8B-Instruct",
+    deployment_status: str = "DEPLOYING",
+) -> dict[str, Any]:
+    return {
+        "adapter": {
+            "id": adapter_id,
+            "displayName": "Checkpoint Adapter",
+            "userId": "user-123",
+            "teamId": None,
+            "rftRunId": "run-123",
+            "baseModel": base_model,
+            "step": 20,
+            "status": "READY",
+            "deploymentStatus": deployment_status,
+            "deployedAt": None,
+            "deploymentError": None,
+            "createdAt": "2026-01-01T00:00:00Z",
+            "updatedAt": "2026-01-01T00:00:00Z",
+        },
+        "message": "Checkpoint adapter deployment started",
+    }
+
 
 def test_deployments_create_prints_chat_and_api_key_commands(monkeypatch) -> None:
     monkeypatch.setenv("PRIME_API_KEY", "dummy")
@@ -57,3 +87,88 @@ def deploy_adapter(self, model_id: str) -> Any:
     assert "export PRIME_API_KEY=<insert_key_here>" in output
     assert "PRIME_API_KEY" in output
     assert "curl -X POST" in output
+
+
+def test_deployments_client_deploy_checkpoint_posts_endpoint() -> None:
+    captured: dict[str, Any] = {}
+
+    class DummyAPIClient:
+        def post(self, endpoint: str, json: dict[str, Any] | None = None) -> dict:
+            captured["endpoint"] = endpoint
+            captured["json"] = json
+            return _adapter_response()
+
+    adapter = DeploymentsClient(DummyAPIClient()).deploy_checkpoint("ckpt-123")
+
+    assert captured["endpoint"] == "/rft/checkpoints/ckpt-123/deploy"
+    assert captured["json"] is None
+    assert adapter.id == "adapter-123"
+
+
+def test_deployments_create_checkpoint_prints_adapter_result(monkeypatch) -> None:
+    monkeypatch.setattr("prime_cli.main.check_for_update", lambda: (False, None))
+
+    adapter = SimpleNamespace(
+        id="adapter-456",
+        base_model="Qwen/Qwen3.5-0.8B",
+        deployment_status="DEPLOYING",
+    )
+
+    class DummyDeploymentsClient:
+        def __init__(self, api_client: Any) -> None:
+            self.api_client = api_client
+
+        def deploy_checkpoint(self, checkpoint_id: str) -> Any:
+            assert checkpoint_id == "ckpt-456"
+            return adapter
+
+    monkeypatch.setattr("prime_cli.commands.deployments.APIClient", lambda: object())
+    monkeypatch.setattr(
+        "prime_cli.commands.deployments.DeploymentsClient",
+        DummyDeploymentsClient,
+    )
+
+    result = runner.invoke(
+        app,
+        ["deployments", "create", "--checkpoint-id", "ckpt-456", "--yes"],
+        env=TEST_ENV,
+    )
+    output = strip_ansi(result.output)
+
+    assert result.exit_code == 0, result.output
+    assert "Deploying checkpoint:" in output
+    assert "Checkpoint ID: ckpt-456" in output
+    assert "Deployment initiated successfully!" in output
+    assert "Adapter ID: adapter-456" in output
+    assert "Status: DEPLOYING" in output
+    assert '"Qwen/Qwen3.5-0.8B:adapter-456"' in output
+    assert "prime deployments list" in output
+
+
+def test_deployments_create_checkpoint_surfaces_conflict_errors(monkeypatch) -> None:
+    monkeypatch.setattr("prime_cli.main.check_for_update", lambda: (False, None))
+
+    class DummyDeploymentsClient:
+        def __init__(self, api_client: Any) -> None:
+            self.api_client = api_client
+
+        def deploy_checkpoint(self, checkpoint_id: str) -> Any:
+            assert checkpoint_id == "ckpt-busy"
+            raise APIError("HTTP 409: Checkpoint adapter preparation is already in progress")
+
+    monkeypatch.setattr("prime_cli.commands.deployments.APIClient", lambda: object())
+    monkeypatch.setattr(
+        "prime_cli.commands.deployments.DeploymentsClient",
+        DummyDeploymentsClient,
+    )
+
+    result = runner.invoke(
+        app,
+        ["deployments", "create", "--checkpoint-id", "ckpt-busy", "--yes"],
+        env=TEST_ENV,
+    )
+    output = strip_ansi(result.output)
+
+    assert result.exit_code == 1
+    assert "Error: HTTP 409" in output
+    assert "Checkpoint adapter preparation is already in progress" in output