--- license: apache-2.0 --- # Bylastic: A Log Classifier Compatible with Elastic ## Introduction **Bylastic** is an advanced AI-based log classification model specifically designed to categorize records into three levels: **ERROR**, **WARNING**, and **INFO**. Created by **Byviz Analytics**, this model is fully optimized for integration with Elastic, offering an efficient and accurate solution for log management and analysis. ## Key Features - **Accurate Classification**: Bylastic classifies logs into three critical categories: **ERROR**, **WARNING**, and **INFO**, helping to quickly identify problems, warnings, and general system information. - **Full Elastic Compatibility**: Designed to seamlessly integrate with Elastic, Bylastic facilitates data ingestion and analysis within the Elastic ecosystem. - **High Performance**: Optimized to process large volumes of logs, ensuring fast and efficient performance even in high-demand environments. - **Easy Integration**: Bylastic can be easily integrated into your existing log processing pipelines, reducing implementation time and associated costs. ### Precision Bylastic vs Bert Precision in categorizing logs with example data, Bert cannot identify the categories ![image/png](https://cdn-uploads.huggingface.co/production/uploads/65bc645cb7db0ab095f10320/hpwBT4dKWt3rIKAjn4UM4.png) ## Requeriments Bylastic vs Bert ![image/png](https://cdn-uploads.huggingface.co/production/uploads/65bc645cb7db0ab095f10320/gpCmIOXPScF4R2LgMre0z.png) ## How It Works Bylastic utilizes advanced natural language processing (NLP) techniques, a branch of artificial intelligence (AI), to analyze and categorize logs. The model has been trained with a diverse set of log data, ensuring high accuracy in classification. ### Log Categories - **ERROR**: Logs indicating critical failures or serious problems that require immediate attention. - **WARNING**: Logs indicating potential issues that could become errors if not properly managed. - **INFO**: Informational logs that provide details about the normal functioning of the system. ## Integration with Elastic Integrating Bylastic with Elastic is straightforward and direct. Here is a quick guide to integrate the model into your Elastic environment: 1. **Installation**: Download Bylastic from Hugging Face. 2. **Upload the Model**: Use `eland` to upload the model to your Elastic cluster. 3. **Create an inference pipeline in Elastic** ## Benefits - **Improved Log Management**: Facilitates the identification and resolution of issues by automatically classifying logs. - **Time Savings**: Reduces the time required to manually review and categorize logs. - **Higher Accuracy**: Minimizes human errors in log classification. - **Easy Integration**: Seamlessly integrates with Elastic, leveraging Elastic's advanced search and analysis capabilities. # Load model directly ```python from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("byviz/bylastic_classification_logs") model = AutoModelForSequenceClassification.from_pretrained("byviz/bylastic_classification_logs") ``` ## Test with Elastic ![image/png](https://cdn-uploads.huggingface.co/production/uploads/65bc645cb7db0ab095f10320/tTaQ_H84CqPR0b3Sl0Thv.png) # Contact If you need AI models with personalized training and compatible with elastic or have any suggestions, you can contact: - **ivan.frias@byviz.com** - **ivan.frias@elastic.co**