Chris Christiansen
9fcb9c354a
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46 lines
1.6 KiB
Python
46 lines
1.6 KiB
Python
# agents/core-logic/heavy_predictor.py
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from google.cloud import bigquery
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# Configuration
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BIGQUERY_PROJECT = "propane-will-491900-m5"
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BIGQUERY_DATASET = "osvauco_logs"
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BIGQUERY_TABLE = "cloud_run_logs"
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TELEMETRY_CALLS_THRESHOLD = 500
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def check_and_trigger_heavy_mode():
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"""
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Checks the number of telemetry calls and triggers heavy mode if the threshold is exceeded.
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"""
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try:
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client = bigquery.Client(project=BIGQUERY_PROJECT)
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table_id = f"{BIGQUERY_PROJECT}.{BIGQUERY_DATASET}.{BIGQUERY_TABLE}"
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# 1. Query the number of telemetry calls from BigQuery
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query = f"""
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SELECT COUNT(*) as total_calls
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FROM `{table_id}`
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WHERE timestamp > TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 24 HOUR)
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"""
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query_job = client.query(query)
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results = query_job.result()
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for row in results:
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total_calls = row.total_calls
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print(f"Total telemetry calls in the last 24 hours: {total_calls}")
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# 2. Trigger heavy mode if the threshold is exceeded
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if total_calls > TELEMETRY_CALLS_THRESHOLD:
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print("Telemetry calls threshold exceeded. Triggering heavy mode.")
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# Placeholder for logic to trigger heavy mode
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# This could involve scaling up resources, switching to a more powerful model, etc.
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pass
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else:
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print("Telemetry calls are within acceptable limits.")
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except Exception as e:
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print(f"An error occurred: {e}")
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if __name__ == "__main__":
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check_and_trigger_heavy_mode()
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