create AWS infra

.gitignore

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+__pycache__/
+.venv/
+config.yaml
+cdk.out/
+.qai-cli-infra*

.python-version

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+3.13

README.md

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+# qai-cli
+
+A CLI for the Qualcomm model MLOps pipeline — browse and download models from Qualcomm AI Hub, fine-tune them on custom datasets using SageMaker, validate inference, and prepare artifacts for Qualcomm hardware deployment.
+
+## Requirements
+
+- Python 3.13+
+- [uv](https://docs.astral.sh/uv/getting-started/installation/)
+- AWS account with credentials configured (`aws configure`) when using `qai-cli infra`
+- AWS CDK CLI (`npm install -g aws-cdk`) when using `qai-cli infra setup` or `qai-cli infra destroy`
+
+## Installation
+
+```bash
+git clone <repo>
+cd qai-cli
+uv sync
+```
+
+Run commands with `uv run qai-cli <command>` or activate the venv first:
+
+```bash
+source .venv/bin/activate
+qai-cli --help
+```
+
+## Quick start
+
+```bash
+# 1. Create config.yaml in the current directory
+qai-cli init
+
+# 2. Edit config.yaml — at minimum set s3.bucket and sagemaker.role_name
+
+# 3. Provision AWS infrastructure (S3 bucket + SageMaker IAM role).
+#    This is the step that requires the AWS CDK CLI.
+qai-cli infra setup
+```
+
+## Configuration
+
+`qai-cli init` writes a `config.yaml` in the current directory. The fields you must fill in before using the tool:
+
+```yaml
+aws:
+  region: us-east-1
+  profile: default          # AWS CLI profile name
+
+s3:
+  bucket: your-unique-bucket-name
+
+sagemaker:
+  role_name: qai-cli-sagemaker-role
+```
+
+To provision an MLflow tracking server, set:
+
+```yaml
+mlflow:
+  mode: create
+  tracking_server_name: your-tracking-server-name
+```
+
+To use an existing MLflow tracking server, set:
+
+```yaml
+mlflow:
+  mode: existing
+  tracking_server_name: your-tracking-server-name
+```
+
+## Commands
+
+### `init`
+
+```
+qai-cli init                  Write config.yaml
+qai-cli init --output <path>  Write config to a custom path
+qai-cli init --force          Overwrite an existing config file
+```
+
+### `infra`
+
+```
+qai-cli infra setup                         Deploy the CDK stack
+qai-cli infra setup --no-bootstrap          Deploy without running CDK bootstrap
+qai-cli infra status                        Show CDK stack/resource status
+qai-cli infra destroy                       Destroy stack, retaining S3 data
+qai-cli infra destroy --yes                 Destroy stack without confirmation
+qai-cli infra destroy --delete-bucket-data  Destroy stack and delete S3 data
+```
+
+## AWS permissions required
+
+The IAM user or role running the CLI needs:
+
+| Action | Service |
+|---|---|
+| CreateBucket, DeleteBucket, PutObject, GetObject, ListBucket, DeleteObject | S3 |
+| CreateRole, GetRole, DeleteRole, AttachRolePolicy, DetachRolePolicy | IAM |
+| CreateStack, UpdateStack, DeleteStack, DescribeStacks, DescribeStackEvents | CloudFormation |
+| GetCallerIdentity | STS |
+| CreateMlflowTrackingServer, DescribeMlflowTrackingServer, DeleteMlflowTrackingServer | SageMaker AI, when `mlflow.mode` is `create` or `existing` |
+
+`AdministratorAccess` covers all of the above.

app.py

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+import os
+
+import aws_cdk as cdk
+
+from src.commands.utils import load_config
+from src.infra.stack import QaiStack
+
+app = cdk.App()
+
+config_path = app.node.try_get_context("config") or "config.yaml"
+stack_name = app.node.try_get_context("stack_name") or "QaiCliStack"
+account_id = app.node.try_get_context("account_id") or os.getenv("CDK_DEFAULT_ACCOUNT")
+delete_bucket_data = str(app.node.try_get_context("delete_bucket_data") or "false").lower() == "true"
+
+cfg = load_config(config_path)
+
+QaiStack(
+    app,
+    stack_name,
+    config=cfg,
+    delete_bucket_data=delete_bucket_data,
+    env=cdk.Environment(
+        account=account_id,
+        region=cfg.aws.region,
+    ),
+)
+
+app.synth()

pyproject.toml

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+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[project]
+name = "qai-cli"
+version = "0.1.0"
+description = "CLI for SageMaker ONNX training and Qualcomm AI Hub optimization"
+requires-python = ">=3.13"
+dependencies = [
+    "aws-cdk-lib>=2.180.0",
+    "typer==0.25.0",
+    "boto3>=1.34,<1.42",
+    "constructs>=10.0.0",
+    "pydantic>=2.13.3",
+    "pyyaml>=6.0.3",
+]
+
+[project.scripts]
+qai-cli = "src.main:app"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src"]
+
+[dependency-groups]
+dev = [
+    "boto3-stubs[iam,s3,sagemaker]",
+    "pyright>=1.1.409",
+    "types-PyYAML",
+    "ruff>=0.4",
+]
+
+[tool.ruff]
+line-length = 123
+
+[tool.ruff.lint]
+select = ["E", "F", "I"]

pyrightconfig.json

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+{
+    "venvPath": ".",
+    "venv": ".venv",
+    "reportMissingModuleSource": "none"
+}

src/aws/cloudformation.py

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+from typing import Any
+
+import boto3
+from botocore.exceptions import ClientError
+
+from src.infra.provisioning import STACK_NAME
+
+
+def stack_status(region: str, profile: str) -> dict[str, Any] | None:
+    client = boto3.Session(profile_name=profile, region_name=region).client("cloudformation")
+    try:
+        stack = client.describe_stacks(StackName=STACK_NAME)["Stacks"][0]
+    except ClientError as e:
+        message = e.response.get("Error", {}).get("Message", "")
+        if "does not exist" in message:
+            return None
+        raise
+    return {
+        "name": stack["StackName"],
+        "status": stack["StackStatus"],
+        "outputs": {item["OutputKey"]: item.get("OutputValue", "") for item in stack.get("Outputs", [])},
+    }

src/aws/identity.py

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+import boto3
+
+
+def account_id(region: str, profile: str) -> str:
+    return boto3.Session(profile_name=profile, region_name=region).client("sts").get_caller_identity()["Account"]

src/aws/mlflow.py

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+from typing import Any, cast
+
+import boto3
+from botocore.exceptions import ClientError
+
+
+def describe_tracking_server(region: str, profile: str, name: str) -> dict[str, Any] | None:
+    client = boto3.Session(profile_name=profile, region_name=region).client("sagemaker")
+    try:
+        return cast(dict[str, Any], client.describe_mlflow_tracking_server(TrackingServerName=name))
+    except ClientError as e:
+        code = e.response.get("Error", {}).get("Code", "")
+        message = e.response.get("Error", {}).get("Message", "")
+        if (
+            code in {"ResourceNotFound", "ResourceNotFoundException", "ValidationException"}
+            or "not found" in message.lower()
+        ):
+            return None
+        raise

src/commands/infra.py

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+from pathlib import Path
+from tempfile import TemporaryDirectory
+
+import typer
+import yaml
+from rich.table import Table
+
+from src.aws import cloudformation, identity, mlflow
+from src.commands.utils import CONFIG_OPT, CONSOLE, load_cfg
+from src.config import Config, MlflowMode
+from src.infra import provisioning
+from src.infra.state import read_infra_state
+
+app = typer.Typer(help="Manage AWS infrastructure")
+
+
+@app.command()
+def setup(
+    config: str = CONFIG_OPT,
+    bootstrap: bool = typer.Option(
+        True,
+        "--bootstrap/--no-bootstrap",
+        help="Run CDK bootstrap before deploying the application stack",
+    ),
+) -> None:
+    """Create infrastructure with AWS CDK."""
+    cfg = load_cfg(config)
+    CONSOLE.print("[bold]Deploying infrastructure with AWS CDK...[/bold]")
+
+    try:
+        account_id = identity.account_id(cfg.aws.region, cfg.aws.profile)
+        if cfg.mlflow.mode is MlflowMode.existing:
+            assert cfg.mlflow.tracking_server_name is not None
+            with CONSOLE.status("Checking MLflow tracking server..."):
+                server = mlflow.describe_tracking_server(
+                    cfg.aws.region,
+                    cfg.aws.profile,
+                    cfg.mlflow.tracking_server_name,
+                )
+            if server is None:
+                raise RuntimeError(f"MLflow tracking server not found: {cfg.mlflow.tracking_server_name}")
+
+        if bootstrap:
+            with CONSOLE.status("Running cdk bootstrap..."):
+                provisioning.bootstrap(
+                    profile=cfg.aws.profile,
+                    account_id=account_id,
+                    region=cfg.aws.region,
+                )
+        with CONSOLE.status("Running cdk deploy..."):
+            state = provisioning.deploy(
+                profile=cfg.aws.profile,
+                account_id=account_id,
+                region=cfg.aws.region,
+                config_path=config,
+                config_dir=str(Path(config).parent),
+                config_snapshot=cfg.model_dump(mode="json"),
+            )
+    except RuntimeError as e:
+        CONSOLE.print(f"[red]{e}[/red]")
+        raise typer.Exit(1)
+
+    outputs = state.get("outputs", {})
+    if outputs.get("DataBucketArn"):
+        CONSOLE.print(f"[green]✓[/green] S3 bucket: {outputs['DataBucketArn']}")
+    if outputs.get("SageMakerRoleArn"):
+        CONSOLE.print(f"[green]✓[/green] IAM role:  {outputs['SageMakerRoleArn']}")
+    if cfg.mlflow.mode is MlflowMode.create and outputs.get("MlflowTrackingServerArn"):
+        CONSOLE.print(f"[green]✓[/green] MLflow:    {outputs['MlflowTrackingServerArn']}")
+    elif cfg.mlflow.mode is MlflowMode.existing:
+        CONSOLE.print(f"[green]✓[/green] MLflow:    {cfg.mlflow.tracking_server_name}")
+    CONSOLE.print("\n[bold green]Infrastructure ready.[/bold green]")
+
+
+@app.command()
+def status(config: str = CONFIG_OPT) -> None:
+    """Show current infrastructure status."""
+    cfg = load_cfg(config)
+    stack = cloudformation.stack_status(cfg.aws.region, cfg.aws.profile)
+
+    table = Table(title="Infrastructure Status")
+    table.add_column("Resource", style="cyan")
+    table.add_column("Name")
+    table.add_column("Status")
+    table.add_column("ARN / URI")
+
+    if not stack:
+        table.add_row("CDK Stack", provisioning.STACK_NAME, "[red]missing[/red]", "-")
+        table.add_row("S3 Bucket", cfg.s3.bucket, "[red]unknown[/red]", "-")
+        table.add_row("IAM Role", cfg.sagemaker.role_name, "[red]unknown[/red]", "-")
+        if cfg.mlflow.mode is not MlflowMode.disabled:
+            table.add_row(
+                "MLflow",
+                cfg.mlflow.tracking_server_name or "-",
+                "[red]unknown[/red]",
+                "-",
+            )
+        CONSOLE.print(table)
+        return
+
+    outputs = stack["outputs"]
+    table.add_row("CDK Stack", stack["name"], f"[green]{stack['status']}[/green]", "-")
+    table.add_row(
+        "S3 Bucket",
+        cfg.s3.bucket,
+        "[green]managed[/green]",
+        outputs.get("DataBucketArn", "-"),
+    )
+    table.add_row(
+        "IAM Role",
+        cfg.sagemaker.role_name,
+        "[green]managed[/green]",
+        outputs.get("SageMakerRoleArn", "-"),
+    )
+    if cfg.mlflow.mode is MlflowMode.create:
+        table.add_row(
+            "MLflow",
+            cfg.mlflow.tracking_server_name or "-",
+            "[green]managed[/green]",
+            outputs.get("MlflowTrackingServerArn", outputs.get("MlflowArtifactUri", "-")),
+        )
+    elif cfg.mlflow.mode is MlflowMode.existing:
+        server = mlflow.describe_tracking_server(
+            cfg.aws.region,
+            cfg.aws.profile,
+            cfg.mlflow.tracking_server_name or "",
+        )
+        if server is None:
+            table.add_row("MLflow", cfg.mlflow.tracking_server_name or "-", "[red]missing[/red]", "-")
+        else:
+            table.add_row(
+                "MLflow",
+                cfg.mlflow.tracking_server_name or "-",
+                f"[green]{server.get('TrackingServerStatus', 'existing')}[/green]",
+                server.get("TrackingServerArn") or server.get("ArtifactStoreUri") or "-",
+            )
+
+    CONSOLE.print(table)
+
+
+@app.command()
+def destroy(
+    config: str = CONFIG_OPT,
+    yes: bool = typer.Option(False, "--yes", "-y", help="Skip confirmation prompt"),
+    delete_bucket_data: bool = typer.Option(
+        False,
+        "--delete-bucket-data",
+        help="Delete stack-managed S3 objects and bucket instead of retaining data",
+    ),
+) -> None:
+    """Destroy the CDK stack."""
+    cfg = _destroy_config(config)
+
+    if not yes and not delete_bucket_data:
+        typer.confirm(
+            f"Destroy CDK stack '{provisioning.STACK_NAME}' while retaining S3 bucket data?",
+            abort=True,
+        )
+
+    try:
+        account_id = _destroy_account_id(config, cfg)
+        with TemporaryDirectory() as temp_dir:
+            snapshot_path = Path(temp_dir) / "config.yaml"
+            snapshot_path.write_text(yaml.safe_dump(cfg.model_dump(mode="json"), sort_keys=False))
+            with CONSOLE.status("Running cdk destroy..."):
+                provisioning.destroy(
+                    profile=cfg.aws.profile,
+                    account_id=account_id,
+                    config_path=str(snapshot_path),
+                    delete_bucket_data=delete_bucket_data,
+                )
+    except RuntimeError as e:
+        CONSOLE.print(f"[red]{e}[/red]")
+        raise typer.Exit(1)
+    CONSOLE.print(f"[green]✓[/green] Destroyed stack: {provisioning.STACK_NAME}")
+
+
+def _destroy_config(config_path: str) -> Config:
+    config_dir = str(Path(config_path).parent)
+    state = read_infra_state(config_dir)
+    config_snapshot = state.get("config")
+    if config_snapshot:
+        return Config.model_validate(config_snapshot)
+    return load_cfg(config_path)
+
+
+def _destroy_account_id(config_path: str, cfg: Config) -> str:
+    config_dir = str(Path(config_path).parent)
+    state = read_infra_state(config_dir)
+    account_id = state.get("aws", {}).get("account_id")
+    if account_id:
+        return str(account_id)
+    return identity.account_id(cfg.aws.region, cfg.aws.profile)

src/commands/utils.py

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+from pathlib import Path
+
+import typer
+import yaml
+from rich.console import Console
+
+from src.config import Config
+
+CONSOLE = Console()
+CONFIG_OPT = typer.Option("config.yaml", "--config", "-c", help="Path to config file")
+
+
+def load_config(path: str = "config.yaml") -> Config:
+    config_path = Path(path)
+    if not config_path.exists():
+        raise FileNotFoundError(
+            f"Config file not found: {config_path}. Run 'qai-cli init' to create one."
+        )
+    with open(config_path) as f:
+        data = yaml.safe_load(f)
+    return Config.model_validate(data)
+
+
+def load_cfg(path: str = "config.yaml") -> Config:
+    try:
+        return load_config(path)
+    except FileNotFoundError as e:
+        CONSOLE.print(f"[red]{e}[/red]")
+        raise typer.Exit(1)

src/config.py

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+from enum import Enum
+from typing import Any, Literal
+
+from mypy_boto3_s3.literals import BucketLocationConstraintType
+from mypy_boto3_sagemaker.literals import TrainingInstanceTypeType
+from pydantic import BaseModel, Field, model_validator
+
+
+class MlflowMode(str, Enum):
+    disabled = "disabled"
+    create = "create"
+    existing = "existing"
+
+
+class MlflowServerSize(str, Enum):
+    small = "Small"
+    medium = "Medium"
+    large = "Large"
+
+
+class AwsConfig(BaseModel):
+    region: BucketLocationConstraintType | Literal["us-east-1"] = "us-east-1"
+    profile: str = "default"
+
+
+class S3Config(BaseModel):
+    bucket: str = "my-onnx-bucket"
+    data_prefix: str = "data/"
+    model_prefix: str = "models/"
+
+
+class TrainingConfig(BaseModel):
+    instance_type: TrainingInstanceTypeType = "ml.m5.xlarge"
+    instance_count: int = 1
+    image_uri: str = ""
+    entry_point: str | None = None
+    source_dir: str | None = None
+    hyperparameters: dict[str, Any] = Field(default_factory=dict)
+
+
+class SageMakerConfig(BaseModel):
+    role_name: str = "qai-cli-sagemaker-role"
+    training: TrainingConfig = Field(default_factory=TrainingConfig)
+
+
+class MlflowConfig(BaseModel):
+    mode: MlflowMode = MlflowMode.disabled
+    tracking_server_name: str | None = None
+    artifact_prefix: str = "mlflow/"
+    tracking_server_size: MlflowServerSize = MlflowServerSize.small
+    mlflow_version: str | None = None
+    automatic_model_registration: bool = False
+    weekly_maintenance_window_start: str | None = None
+
+    @model_validator(mode="after")
+    def require_tracking_server_name(self) -> "MlflowConfig":
+        if self.mode in {MlflowMode.create, MlflowMode.existing} and not self.tracking_server_name:
+            raise ValueError("mlflow.tracking_server_name is required when mlflow.mode is create or existing")
+        return self
+
+
+class Config(BaseModel):
+    aws: AwsConfig = Field(default_factory=AwsConfig)
+    s3: S3Config = Field(default_factory=S3Config)
+    sagemaker: SageMakerConfig = Field(default_factory=SageMakerConfig)
+    mlflow: MlflowConfig = Field(default_factory=MlflowConfig)

src/infra/provisioning.py

@@ -0,0 +1,118 @@
+import json
+import subprocess
+from pathlib import Path
+from typing import Any
+
+from src.infra.state import state_path, write_infra_state
+
+STACK_NAME = "QaiCliStack"
+
+
+def bootstrap(*, profile: str, account_id: str, region: str) -> None:
+    _run(["cdk", "bootstrap", f"aws://{account_id}/{region}", "--profile", profile])
+
+
+def deploy(
+    *,
+    profile: str,
+    account_id: str,
+    region: str,
+    config_path: str,
+    config_dir: str,
+    config_snapshot: dict[str, Any],
+) -> dict[str, Any]:
+    outputs_file = state_path(config_dir).with_suffix(".cdk-outputs.json")
+    cmd = _cdk_cmd(
+        "deploy",
+        profile=profile,
+        account_id=account_id,
+        config_path=config_path,
+        delete_bucket_data=False,
+    ) + ["--require-approval", "never", "--outputs-file", str(outputs_file)]
+    _run(cmd)
+
+    outputs = _read_outputs(outputs_file)
+    state = {
+        "stack_name": STACK_NAME,
+        "aws": {
+            "account_id": account_id,
+            "region": region,
+            "profile": profile,
+        },
+        "config": config_snapshot,
+        "outputs": outputs,
+    }
+    write_infra_state(config_dir, state)
+    return state
+
+
+def destroy(
+    *,
+    profile: str,
+    account_id: str,
+    config_path: str,
+    delete_bucket_data: bool,
+) -> None:
+    if delete_bucket_data:
+        update_cmd = _cdk_cmd(
+            "deploy",
+            profile=profile,
+            account_id=account_id,
+            config_path=config_path,
+            delete_bucket_data=True,
+        ) + ["--require-approval", "never"]
+        _run(update_cmd)
+
+    cmd = _cdk_cmd(
+        "destroy",
+        profile=profile,
+        account_id=account_id,
+        config_path=config_path,
+        delete_bucket_data=delete_bucket_data,
+    ) + ["--force"]
+    _run(cmd)
+
+
+def _cdk_cmd(
+    action: str,
+    *,
+    profile: str,
+    account_id: str,
+    config_path: str,
+    delete_bucket_data: bool,
+) -> list[str]:
+    cmd = [
+        "cdk",
+        action,
+        STACK_NAME,
+        "--app",
+        "python app.py",
+        "--profile",
+        profile,
+        "-c",
+        f"account_id={account_id}",
+        "-c",
+        f"config={config_path}",
+        "-c",
+        f"stack_name={STACK_NAME}",
+        "-c",
+        f"delete_bucket_data={str(delete_bucket_data).lower()}",
+    ]
+    return cmd
+
+
+def _run(cmd: list[str]) -> None:
+    try:
+        subprocess.run(cmd, check=True)
+    except FileNotFoundError as e:
+        raise RuntimeError("CDK CLI not found. Install it with: npm install -g aws-cdk") from e
+    except subprocess.CalledProcessError as e:
+        raise RuntimeError(f"CDK command failed with exit code {e.returncode}.") from e
+
+
+def _read_outputs(path: Path) -> dict[str, str]:
+    if not path.exists():
+        return {}
+    with open(path) as f:
+        data = json.load(f)
+    return data.get(STACK_NAME, {})

src/infra/stack.py

@@ -0,0 +1,169 @@
+from typing import Any
+
+from aws_cdk import CfnOutput, RemovalPolicy, Stack
+from aws_cdk import aws_iam as iam
+from aws_cdk import aws_s3 as s3
+from aws_cdk import aws_sagemaker as sagemaker
+from constructs import Construct
+
+from src.config import Config, MlflowMode
+
+
+class QaiStack(Stack):
+    def __init__(
+        self,
+        scope: Construct,
+        construct_id: str,
+        *,
+        config: Config,
+        delete_bucket_data: bool = False,
+        **kwargs,
+    ) -> None:
+        super().__init__(scope, construct_id, **kwargs)
+
+        removal_policy = RemovalPolicy.DESTROY if delete_bucket_data else RemovalPolicy.RETAIN
+        data_bucket = s3.Bucket(
+            self,
+            "DataBucket",
+            bucket_name=config.s3.bucket,
+            versioned=True,
+            removal_policy=removal_policy,
+            auto_delete_objects=delete_bucket_data,
+        )
+
+        role = iam.CfnRole(
+            self,
+            "SageMakerRole",
+            role_name=config.sagemaker.role_name,
+            assume_role_policy_document=self._sagemaker_trust_policy(),
+            managed_policy_arns=[
+                f"arn:{self.partition}:iam::aws:policy/AmazonSageMakerFullAccess",
+            ],
+        )
+        iam.CfnPolicy(
+            self,
+            "SageMakerRoleS3Policy",
+            roles=[role.ref],
+            policy_name="SageMakerRoleS3Policy",
+            policy_document={
+                "Version": "2012-10-17",
+                "Statement": [{
+                    "Effect": "Allow",
+                    "Action": [
+                        "s3:GetObject*",
+                        "s3:GetBucket*",
+                        "s3:List*",
+                        "s3:DeleteObject*",
+                        "s3:PutObject",
+                        "s3:PutObjectLegalHold",
+                        "s3:PutObjectRetention",
+                        "s3:PutObjectTagging",
+                        "s3:PutObjectVersionTagging",
+                        "s3:Abort*",
+                    ],
+                    "Resource": [
+                        data_bucket.bucket_arn,
+                        f"{data_bucket.bucket_arn}/*",
+                    ],
+                }],
+            },
+        )
+
+        CfnOutput(self, "DataBucketName", value=data_bucket.bucket_name)
+        CfnOutput(self, "DataBucketArn", value=data_bucket.bucket_arn)
+        CfnOutput(self, "SageMakerRoleArn", value=role.attr_arn)
+
+        if config.mlflow.mode is MlflowMode.create:
+            artifact_prefix = config.mlflow.artifact_prefix.strip("/")
+            artifact_uri = (
+                f"s3://{data_bucket.bucket_name}/{artifact_prefix}/"
+                if artifact_prefix
+                else f"s3://{data_bucket.bucket_name}/"
+            )
+            mlflow_role = iam.CfnRole(
+                self,
+                "MlflowRole",
+                assume_role_policy_document=self._sagemaker_trust_policy(),
+            )
+            s3_statement: dict[str, Any] = {
+                "Effect": "Allow",
+                "Action": [
+                    "s3:GetObject*",
+                    "s3:GetBucket*",
+                    "s3:List*",
+                    "s3:DeleteObject*",
+                    "s3:PutObject",
+                    "s3:PutObjectLegalHold",
+                    "s3:PutObjectRetention",
+                    "s3:PutObjectTagging",
+                    "s3:PutObjectVersionTagging",
+                    "s3:Abort*",
+                ],
+                "Resource": [
+                    data_bucket.bucket_arn,
+                    (
+                        f"{data_bucket.bucket_arn}/{artifact_prefix}/*"
+                        if artifact_prefix
+                        else f"{data_bucket.bucket_arn}/*"
+                    ),
+                ],
+            }
+            list_statement: dict[str, Any] = {
+                "Effect": "Allow",
+                "Action": "s3:ListBucket",
+                "Resource": data_bucket.bucket_arn,
+            }
+            if artifact_prefix:
+                list_statement["Condition"] = {"StringLike": {"s3:prefix": [f"{artifact_prefix}/*"]}}
+            iam.CfnPolicy(
+                self,
+                "MlflowRolePolicy",
+                roles=[mlflow_role.ref],
+                policy_name="MlflowRolePolicy",
+                policy_document={
+                    "Version": "2012-10-17",
+                    "Statement": [
+                        s3_statement,
+                        list_statement,
+                        {
+                            "Effect": "Allow",
+                            "Action": [
+                                "sagemaker:AddTags",
+                                "sagemaker:CreateModelPackageGroup",
+                                "sagemaker:CreateModelPackage",
+                                "sagemaker:UpdateModelPackage",
+                                "sagemaker:DescribeModelPackageGroup",
+                            ],
+                            "Resource": "*",
+                        },
+                    ],
+                },
+            )
+
+            tracking_server = sagemaker.CfnMlflowTrackingServer(
+                self,
+                "MlflowTrackingServer",
+                artifact_store_uri=artifact_uri,
+                role_arn=mlflow_role.attr_arn,
+                tracking_server_name=config.mlflow.tracking_server_name or "",
+                automatic_model_registration=config.mlflow.automatic_model_registration,
+                mlflow_version=config.mlflow.mlflow_version,
+                tracking_server_size=config.mlflow.tracking_server_size.value,
+                weekly_maintenance_window_start=config.mlflow.weekly_maintenance_window_start,
+            )
+
+            CfnOutput(self, "MlflowTrackingServerName", value=config.mlflow.tracking_server_name or "")
+            CfnOutput(self, "MlflowTrackingServerArn", value=tracking_server.attr_tracking_server_arn)
+            CfnOutput(self, "MlflowArtifactUri", value=artifact_uri)
+            CfnOutput(self, "MlflowRoleArn", value=mlflow_role.attr_arn)
+
+    @staticmethod
+    def _sagemaker_trust_policy() -> dict[str, Any]:
+        return {
+            "Version": "2012-10-17",
+            "Statement": [{
+                "Effect": "Allow",
+                "Principal": {"Service": "sagemaker.amazonaws.com"},
+                "Action": "sts:AssumeRole",
+            }],
+        }

src/infra/state.py

@@ -0,0 +1,22 @@
+import json
+from pathlib import Path
+from typing import Any
+
+INFRA_STATE_FILE = ".qai-cli-infra.json"
+
+
+def state_path(config_dir: str) -> Path:
+    return Path(config_dir) / INFRA_STATE_FILE
+
+
+def read_infra_state(config_dir: str) -> dict[str, Any]:
+    path = state_path(config_dir)
+    if not path.exists():
+        return {}
+    with open(path) as f:
+        return json.load(f)
+
+
+def write_infra_state(config_dir: str, state: dict[str, Any]) -> None:
+    with open(state_path(config_dir), "w") as f:
+        json.dump(state, f, indent=2)

src/main.py

@@ -0,0 +1,39 @@
+from pathlib import Path
+
+import typer
+import yaml
+from rich.console import Console
+
+from src.commands import infra
+from src.config import Config
+
+app = typer.Typer(
+    help="qai-cli: End-to-end model managment for Qualcomm AI Hub.",
+    no_args_is_help=True,
+)
+app.add_typer(infra.app, name="infra")
+
+console = Console()
+
+
+@app.command()
+def init(
+    output: str = typer.Option("config.yaml", help="Destination path for the config file"),
+    force: bool = typer.Option(False, "--force", "-f", help="Overwrite an existing config file"),
+) -> None:
+    """Write a starter config.yaml to the current directory."""
+    dest = Path(output)
+    if dest.exists() and not force:
+        console.print(f"[yellow]{dest} already exists.[/yellow] Use --force to overwrite.")
+        raise typer.Exit(1)
+
+    config = Config()
+    dest.parent.mkdir(parents=True, exist_ok=True)
+    with open(dest, "w") as f:
+        yaml.safe_dump(config.model_dump(mode="json"), f, sort_keys=False)
+
+    console.print(f"[green]✓[/green] Config written to [bold]{dest}[/bold]")
+    console.print(
+        "Edit it (especially [cyan]s3.bucket[/cyan] and [cyan]sagemaker.training.image_uri[/cyan]) "
+        "before running other commands."
+    )

uv.lock

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+]
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