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LogSentinelAI leverages LLM with Declarative Extraction to analyze security events, anomalies, and errors from various logs including Apache, Linux, and converts them into structured data that can be visualized with Elasticsearch/Kibana. Simply declare your desired result structure as a Pydantic class, and the AI automatically analyzes logs to return JSON matching that schema. No complex parsing is required.
In each analyzer script, simply declare the desired result structure as a Pydantic class, and the LLM will automatically analyze logs and return results as JSON matching that schema. No complex parsing or post-processing—just declare what you want, and the AI handles the rest. This approach enables developers to focus on "what to extract" declaratively, while the LLM takes care of "how to extract"—a modern paradigm for information extraction.
For installation, environment setup, CLI usage, Elasticsearch/Kibana integration, and all practical guides for LogSentinelAI, please refer to the installation documentation below.
