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fix: remove broken WAA submodule, embed startup script #22

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Merged
abrichr merged 1 commit into from
Feb 13, 2026
Merged

fix: remove broken WAA submodule, embed startup script #22

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3 changes: 0 additions & 3 deletions .gitmodules
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258 changes: 87 additions & 171 deletions openadapt_ml/benchmarks/cli.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3004,14 +3004,29 @@ def cmd_logs(args):
return 0


def upload_startup_script_to_datastore(script_path: str, file_path: str) -> bool:
# Minimal startup script for Azure ML compute instances.
# Previously lived at vendor/WindowsAgentArena/scripts/azure_files/compute-instance-startup.sh
COMPUTE_INSTANCE_STARTUP_SH = """\
#!/bin/bash

# Minimal startup script - completes quickly to avoid Azure ML timeout
# The actual work (Docker pull, Windows boot) happens in the job itself

echo "$(date): Compute instance startup script - minimal version"

# Just exit successfully - the job will handle Docker setup
exit 0
"""


def upload_startup_script_to_datastore(script_content: str, file_path: str) -> bool:
"""Upload startup script to Azure ML workspace code file share.

Azure ML mounts the 'code-*' file share at:
/mnt/batch/tasks/shared/LS_root/mounts/clusters/<instance>/code/

Args:
script_path: Local path to the startup script
script_content: Content of the startup script
file_path: Destination path in file share (e.g., 'Users/openadapt/compute-instance-startup.sh')

Returns:
Expand Down Expand Up @@ -3145,28 +3160,35 @@ def upload_startup_script_to_datastore(script_path: str, file_path: str) -> bool
)
# Ignore errors - directory may already exist

# Upload the script to file share
log("AZURE-ML", f"Uploading {script_path} to {file_path}...")
result = subprocess.run(
[
"az",
"storage",
"file",
"upload",
"--account-name",
storage_account,
"--account-key",
storage_key,
"--share-name",
code_share,
"--source",
script_path,
"--path",
file_path,
],
capture_output=True,
text=True,
)
# Write content to a temp file for az storage upload
with tempfile.NamedTemporaryFile(mode="w", suffix=".sh", delete=False) as tmp:
tmp.write(script_content)
tmp_path = tmp.name

try:
log("AZURE-ML", f"Uploading startup script to {file_path}...")
result = subprocess.run(
[
"az",
"storage",
"file",
"upload",
"--account-name",
storage_account,
"--account-key",
storage_key,
"--share-name",
code_share,
"--source",
tmp_path,
"--path",
file_path,
],
capture_output=True,
text=True,
)
finally:
os.unlink(tmp_path)

if result.returncode != 0:
log("AZURE-ML", f"ERROR: Failed to upload: {result.stderr}")
Expand Down Expand Up @@ -3354,9 +3376,11 @@ def upload_golden_image_to_blob(source_path: str) -> bool:
if not source_dir.exists():
log("AZURE-ML", f"ERROR: Source directory not found: {source_dir}")
log("AZURE-ML", "")
log("AZURE-ML", "You need to prepare the golden image first:")
log("AZURE-ML", " cd vendor/WindowsAgentArena")
log("AZURE-ML", " ./scripts/run.sh --prepare-image true")
log("AZURE-ML", "You need to prepare the golden image first.")
log(
"AZURE-ML",
"See https://github.com/microsoft/WindowsAgentArena for setup instructions.",
)
return False

# Check for required files (only data.img is truly required, OVMF files come from Docker image)
Expand Down Expand Up @@ -4634,74 +4658,22 @@ class CreateArgs:
if skip_benchmark:
log("AUTO", " Skipping benchmark (--skip-benchmark specified)")
else:
# Ensure startup script is uploaded
waa_scripts = (
Path(__file__).parent.parent.parent
/ "vendor"
/ "WindowsAgentArena"
/ "scripts"
)
startup_script_local = (
waa_scripts / "azure_files" / "compute-instance-startup.sh"
)
# Upload embedded startup script
startup_script_datastore_path = "Users/openadapt/compute-instance-startup.sh"

if startup_script_local.exists():
log("AUTO", " Ensuring startup script is uploaded...")
success = upload_startup_script_to_datastore(
str(startup_script_local), startup_script_datastore_path
)
if not success:
log("AUTO", " WARNING: Failed to upload startup script")
# Continue anyway - it might already be there

# Update config.json
config_path = waa_scripts.parent / "config.json"
config = {
"OPENAI_API_KEY": settings.openai_api_key,
"AZURE_SUBSCRIPTION_ID": settings.azure_subscription_id,
"AZURE_ML_RESOURCE_GROUP": settings.azure_ml_resource_group,
"AZURE_ML_WORKSPACE_NAME": settings.azure_ml_workspace_name,
}
with open(config_path, "w") as f:
json.dump(config, f, indent=4)
log("AUTO", f" Updated {config_path}")

# Build run_azure.py command
exp_name = (
getattr(args, "exp_name", None) or f"e{datetime.now().strftime('%m%d%H%M')}"
log("AUTO", " Ensuring startup script is uploaded...")
success = upload_startup_script_to_datastore(
COMPUTE_INSTANCE_STARTUP_SH, startup_script_datastore_path
)
docker_image = getattr(args, "image", None) or "windowsarena/winarena:latest"
model = getattr(args, "model", None) or "gpt-4o-mini"
agent = getattr(args, "agent", None) or "navi"

cmd = [
"python",
str(waa_scripts / "run_azure.py"),
"--docker_img_name",
docker_image,
"--num_workers",
str(num_workers),
"--exp_name",
exp_name,
"--model_name",
model,
"--agent",
agent,
"--ci_startup_script_path",
startup_script_datastore_path,
]

log("AUTO", f" Running: {' '.join(cmd)}")
log("AUTO", f" Workers: {num_workers}, Model: {model}")
log("AUTO", "")

# Run the command
result = subprocess.run(cmd, cwd=waa_scripts)
if not success:
log("AUTO", " WARNING: Failed to upload startup script")
# Continue anyway - it might already be there

if result.returncode != 0:
log("AUTO", " ERROR: run_azure.py failed")
return 1
log(
"AUTO",
" ERROR: run-azure-ml-auto requires vendor/WindowsAgentArena submodule "
"(removed). Use pool-create + pool-run instead.",
)
return 1

# =========================================================================
# Complete
Expand Down Expand Up @@ -4733,7 +4705,6 @@ def cmd_run_azure_ml(args):
Uses --setup to upload the required startup script to Azure datastore.
"""
init_logging()
start_time = time.time()

from openadapt_ml.config import settings

Expand Down Expand Up @@ -4769,17 +4740,7 @@ def cmd_run_azure_ml(args):
)
return 1

# Paths
waa_scripts = (
Path(__file__).parent.parent.parent / "vendor" / "WindowsAgentArena" / "scripts"
)
if not waa_scripts.exists():
log("AZURE-ML", f"ERROR: WAA scripts not found at {waa_scripts}")
return 1

# Startup script configuration
startup_script_local = waa_scripts / "azure_files" / "compute-instance-startup.sh"
# Use custom path or default to Users/openadapt/...
# Startup script datastore path
startup_script_datastore_path = (
getattr(args, "ci_startup_script_path", None)
or "Users/openadapt/compute-instance-startup.sh"
Expand All @@ -4792,14 +4753,8 @@ def cmd_run_azure_ml(args):
"=== SETUP MODE: Uploading startup script to Azure ML datastore ===",
)

if not startup_script_local.exists():
log(
"AZURE-ML", f"ERROR: Startup script not found at {startup_script_local}"
)
return 1

success = upload_startup_script_to_datastore(
str(startup_script_local), startup_script_datastore_path
COMPUTE_INSTANCE_STARTUP_SH, startup_script_datastore_path
)

if success:
Expand Down Expand Up @@ -4861,7 +4816,7 @@ def cmd_run_azure_ml(args):
log("AZURE-ML", "To upload golden image:")
log(
"AZURE-ML",
" 1. Prepare locally: cd vendor/WindowsAgentArena && ./scripts/run.sh --prepare-image true",
" 1. Prepare locally: clone WindowsAgentArena and run ./scripts/run.sh --prepare-image true",
)
log(
"AZURE-ML",
Expand All @@ -4882,11 +4837,11 @@ def cmd_run_azure_ml(args):
if getattr(args, "upload_image", False):
log("AZURE-ML", "=== UPLOAD IMAGE: Uploading golden image to blob storage ===")

# Determine source path
default_source = (
waa_scripts.parent / "src" / "win-arena-container" / "vm" / "storage"
)
source_path = getattr(args, "image_source", None) or str(default_source)
# Determine source path (--image-source required since submodule was removed)
source_path = getattr(args, "image_source", None)
if not source_path:
log("AZURE-ML", "ERROR: --image-source is required (no default path)")
return 1

success = upload_golden_image_to_blob(source_path)
if success:
Expand Down Expand Up @@ -4954,59 +4909,20 @@ def cmd_run_azure_ml(args):
teardown_azure_ml_resources(confirm=confirm, keep_image=keep_image)
return 0

# Update config.json with our settings
config_path = waa_scripts.parent / "config.json"
config = {
"OPENAI_API_KEY": settings.openai_api_key,
"AZURE_SUBSCRIPTION_ID": settings.azure_subscription_id,
"AZURE_ML_RESOURCE_GROUP": settings.azure_ml_resource_group,
"AZURE_ML_WORKSPACE_NAME": settings.azure_ml_workspace_name,
}
with open(config_path, "w") as f:
json.dump(config, f, indent=4)
log("AZURE-ML", f"Updated {config_path}")

# Build run_azure.py command
num_workers = getattr(args, "workers", None) or 1
# Keep exp_name short - compute instance name is "w{worker_id}Exp{exp_name}" and max 24 chars
exp_name = (
getattr(args, "exp_name", None) or f"e{datetime.now().strftime('%m%d%H%M')}"
)
docker_image = getattr(args, "image", None) or "windowsarena/winarena:latest"
model = getattr(args, "model", None) or "gpt-4o-mini"
agent = getattr(args, "agent", None) or "navi"

cmd = [
"python",
str(waa_scripts / "run_azure.py"),
"--docker_img_name",
docker_image,
"--num_workers",
str(num_workers),
"--exp_name",
exp_name,
"--model_name",
model,
"--agent",
agent,
"--ci_startup_script_path",
startup_script_datastore_path,
]

log("AZURE-ML", f"Running: {' '.join(cmd)}")
log("AZURE-ML", f"Workers: {num_workers}, Model: {model}, Image: {docker_image}")
log("AZURE-ML", f"Startup script: {startup_script_datastore_path}")

# Run the command
result = subprocess.run(cmd, cwd=waa_scripts)

elapsed = time.time() - start_time
if result.returncode != 0:
log("AZURE-ML", f"ERROR: run_azure.py failed after {elapsed:.1f}s")
return 1

log("AZURE-ML", f"Completed in {elapsed:.1f}s")
return 0
# Direct benchmark execution via run_azure.py is no longer available
# (vendor/WindowsAgentArena submodule was removed). Use pool commands instead.
log(
"AZURE-ML", "ERROR: Direct Azure ML benchmark execution is no longer available."
)
log("AZURE-ML", "The vendor/WindowsAgentArena submodule has been removed.")
log("AZURE-ML", "")
log("AZURE-ML", "Use pool-based execution instead:")
log(
"AZURE-ML",
" uv run python -m openadapt_ml.benchmarks.cli pool-create --workers N",
)
log("AZURE-ML", " uv run python -m openadapt_ml.benchmarks.cli pool-run --tasks N")
return 1


def get_azure_ml_dedicated_quota(subscription_id: str, location: str) -> dict:
Expand Down Expand Up @@ -7956,7 +7872,7 @@ def main():
)
p_azure_ml.add_argument(
"--image-source",
help="Custom source path for golden image upload (default: vendor/WindowsAgentArena/src/win-arena-container/vm/storage)",
help="Source path for golden image upload (required for --upload-image)",
)
p_azure_ml.add_argument(
"--upload-placeholder",
Expand Down
1 change: 0 additions & 1 deletion vendor/WindowsAgentArena
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Submodule WindowsAgentArena deleted from a956c5