Enhanced URL Classification and Error Handling

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📅 2024-07-11 — Session: Enhanced URL Classification and Error Handling

🕒 21:20–23:30
🏷️ Labels: Url Classification, Error Handling, Openai Api, Python, Elasticsearch
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to integrate and enhance various components of a URL classification system using OpenAI’s API, focusing on improving error handling and data processing.

Key Activities

  • Integrated BERT with Elasticsearch for text classification.
  • Developed a comprehensive workflow for creating a knowledge web, including data collection, processing, and visualization.
  • Implemented an AI agent using GPT-4 for dataset labeling to fine-tune a BERT model.
  • Developed a Python-based URL classification system using OpenAI API, including class definition and example usage.
  • Addressed errors in the URLClassifier class, specifically fixing argument errors in the construct_prompt method and handling null values in input fields.
  • Enhanced HTML cleaning using BeautifulSoup to improve text extraction quality.
  • Implemented robust error handling in DataFrame classification using try-except blocks.
  • Improved entity recognition using spaCy by refining extraction processes and filtering irrelevant content.

Achievements

  • Successfully integrated BERT with Elasticsearch and developed a comprehensive knowledge web workflow.
  • Implemented a robust URL classification system with enhanced error handling.
  • Improved data processing and entity recognition techniques using Python and spaCy.

Pending Tasks

  • Further testing and validation of the enhanced URL classification system.
  • Optimization of the knowledge web workflow for scalability and performance.

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