Use Case: Accessing and storing Workflow Data in Artifact File Directory
Learn about accessing and storing Workflow Data in the Artifact File Directory.
import os
import pandas as pd
import json
def run_tool(config, args):
# ✅ Read input from workflow data directory
workflow_data_dir = os.environ.get('WORKFLOW_DATA_DIRECTORY', '/workflow_data')
input_file = os.path.join(workflow_data_dir, 'sales_data.csv')
if not os.path.exists(input_file):
return {"error": f"Input file not found: {input_file}"}
# Process data
df = pd.read_csv(input_file)
summary = df.groupby('category').sum()
# ✅ Write output to artifact file directory (using relative path)
output_file = "sales_summary.csv"
summary.to_csv(output_file, index=True)
# ✅ Write JSON report to artifact file directory
report_file = "report.json"
with open(report_file, 'w') as f:
json.dump({
"status": "success",
"total_rows": len(df),
"categories": summary.index.tolist()
}, f, indent=2)
# Both files are automatically visible in Agent Studio UI
return {
"status": "success",
"output_files": [output_file, report_file],
"message": "Files created in artifact file directory"
}
