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    Essay Grading Agent

    This notebook presents an automated essay grading system implemented using LangGraph and an LLM model. The system evaluates essays based on four key criteria: relevance, grammar, structure, and depth of analysis.

    Automated essay grading systems can significantly streamline the assessment process in educational settings, providing consistent and objective evaluations. This implementation aims to demonstrate how large language models and graph-based workflows can be combined to create a sophisticated grading system.

    What you'll learn

    • 1
      State Graph: Defines the workflow of the grading process
    • 2
      LLM Model: Provides the underlying language understanding and analysis
    • 3
      Grading Functions: Separate functions for each evaluation criterion
    • 4
      Conditional Logic: Determines the flow of the grading process based on interim scores

    About this tutorial

    This hands-on Jupyter notebook is part of GenAI Agents, a free open-source repository by Nir Diamant covering ai agents techniques with runnable code examples and detailed explanations.

    Free and open-sourceRunnable Jupyter notebookActive community support
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