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Update sample_redteam_evaluations.py to use OS temp folder for output files #44928

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Merged
dargilco merged 2 commits into from
Jan 30, 2026
Merged

Update sample_redteam_evaluations.py to use OS temp folder for output files #44928

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dargilco Jan 30, 2026
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dargilco Jan 30, 2026
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17 changes: 4 additions & 13 deletions sdk/ai/azure-ai-projects/samples/evaluations/sample_redteam_evaluations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,12 +19,11 @@
Set these environment variables with your own values:
1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
Microsoft Foundry project. It has the form: https://<account_name>.services.ai.azure.com/api/projects/<project_name>.
2) DATA_FOLDER - Optional. The folder path where the data files for upload are located.
3) AZURE_AI_AGENT_NAME - Required. The name of the Agent to perform red teaming evaluation on.
2) AZURE_AI_AGENT_NAME - Required. The name of the Agent to perform red teaming evaluation on.
"""

import os

import tempfile
from dotenv import load_dotenv
from pprint import pprint
from azure.ai.projects.models._models import PromptAgentDefinition
Expand All @@ -49,10 +48,6 @@ def main() -> None:
endpoint = os.environ.get("AZURE_AI_PROJECT_ENDPOINT", "")
agent_name = os.environ.get("AZURE_AI_AGENT_NAME", "")

# Construct the paths to the data folder and data file used in this sample
script_dir = os.path.dirname(os.path.abspath(__file__))
data_folder = os.environ.get("DATA_FOLDER", os.path.join(script_dir, "data_folder"))

with (
DefaultAzureCredential() as credential,
AIProjectClient(endpoint=endpoint, credential=credential) as project_client,
Expand Down Expand Up @@ -99,9 +94,7 @@ def main() -> None:
)

taxonomy = project_client.evaluation_taxonomies.create(name=agent_name, body=eval_taxonomy_input)
taxonomy_path = os.path.join(data_folder, f"taxonomy_{agent_name}.json")
# Create the data folder if it doesn't exist
os.makedirs(data_folder, exist_ok=True)
taxonomy_path = os.path.join(tempfile.gettempdir(), f"taxonomy_{agent_name}.json")
with open(taxonomy_path, "w") as f:
f.write(json.dumps(_to_json_primitive(taxonomy), indent=2))
print(f"Red teaming Taxonomy created for agent: {agent_name}. Taxonomy written to {taxonomy_path}")
Expand Down Expand Up @@ -134,9 +127,7 @@ def main() -> None:
run = client.evals.runs.retrieve(run_id=eval_run_response.id, eval_id=eval_object.id)
if run.status == "completed" or run.status == "failed":
output_items = list(client.evals.runs.output_items.list(run_id=run.id, eval_id=eval_object.id))
output_items_path = os.path.join(data_folder, f"redteam_eval_output_items_{agent_name}.json")
# Create the data folder if it doesn't exist
os.makedirs(data_folder, exist_ok=True)
output_items_path = os.path.join(tempfile.gettempdir(), f"redteam_eval_output_items_{agent_name}.json")
with open(output_items_path, "w") as f:
f.write(json.dumps(_to_json_primitive(output_items), indent=2))
print(
Expand Down
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