Week 12: Controlling and Structuring LLM Outputs

Week 12: Controlling and Structuring LLM Outputs#

Overview#

Week 12 focuses on techniques and strategies for controlling and structuring outputs from Large Language Models (LLMs). We’ll explore methods to ensure consistent, reliable, and well-formatted responses from LLMs, making them more suitable for practical applications.

Learning Objectives#

  • Understand different techniques for output structuring in LLMs

  • Learn how to implement prompt engineering for controlled outputs

  • Master methods for formatting and validating LLM responses

  • Explore JSON, XML, and other structured output formats

  • Develop strategies for handling and parsing LLM outputs in applications

Key Topics#

  1. Output Structuring Techniques

    • Template-based outputs

    • JSON and XML formatting

    • Markdown and other markup languages

  2. Control Mechanisms

    • Temperature and sampling parameters

    • Stop sequences and length constraints

    • Format enforcement strategies

  3. Validation and Error Handling

    • Output validation techniques

    • Error detection and correction

    • Fallback mechanisms

Practical Component#

Students will work on implementing various output control mechanisms:

  • Design prompts for structured outputs

  • Create validation systems for LLM responses

  • Build parsers for different output formats

  • Implement error handling for malformed outputs

Assignment#

Create a system that:

  1. Implements at least three different output structuring methods

  2. Includes validation for each output format

  3. Handles errors gracefully

  4. Demonstrates practical use cases for structured outputs

Looking Ahead#

Next week will focus on the final project presentations and course wrap-up, where we’ll apply all the concepts learned throughout the course.