Efficiently debug production issues with advanced anomaly detection and root cause analysis
LogAgent is an open-source tool that leverages Large Language Models (LLMs) to analyze log files, interpret event flows, and identify subtle anomalies that traditional error detection methods might miss.
It's specifically designed to address complex logic and business flow issues in production environments, significantly reducing the time required for issue diagnosis and resolution.
Utilizes state-of-the-art language models for advanced pattern recognition in log data
Identifies logic issues and business flow anomalies that don't trigger traditional error alerts
Efficiently handles log files up to 256k tokens, suitable for extensive production logs
Provides detailed analysis considering the full context of the application's behavior
Fully customizable and extensible to fit specific organizational needs
Accelerates issue resolution by pinpointing the underlying causes of production problems
Unfulfilled orders for PROD-X in the AMER region, potentially due to inventory or fulfillment issues.
import logagent
# Initialize LogAgent
agent = logagent.LogAgent()
# Load and analyze log file
analysis = agent.analyze("path/to/logfile.log")
# Get key insights
insights = analysis.get_insights()
# Print root cause
print("Root Cause:", analysis.get_root_cause())
# Get recommended actions
actions = analysis.get_recommended_actions()
# Visualize log level distribution
analysis.plot_log_level_distribution()