Pseudolang Prompts Unleashed
  • 🖥️Introduction to pseudoLang Prompts
    • Purpose of pseudoLang for ChatGPT
    • Benefits of using pseudoLang
    • Limitations and considerations
  • 🏗️Basic Syntax and Structure
    • Defining Functions
  • Specifying Input Types and Output
  • Indicating Actions and Steps
  • Nesting and loops
  • 🎯Examples of pseudoLang Functions
    • Sample Functions
  • 🌟Tips for Writing Effective Pseudolang Prompts
    • Provide Clear Instructions
  • Defining Input and Output Requirements
  • Using Appropriate Syntax and Formatting
  • Experimenting with Different Phrasings
  • Verifying and Refining Generated Outputs
  • 🧠Advanced pseudoLang Techniques
    • Creating Custom Functions
  • Combining Multiple Functions
  • Handling Errors and Exceptions
  • Guiding the Model with Additional Context
  • 🔚Conclusion and Next Steps
    • Further Resources and Learning
    • Community Contributions and Collaboration
  • Ongoing Development and Future Updates
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Handling Errors and Exceptions

Incorporating error handling or exception-catching steps within your pseudolang prompts can help manage potential issues and improve the reliability of the generated output. By anticipating possible problems and providing instructions on how to address them, you can guide ChatGPT to deliver more accurate and robust responses even when facing uncertainties or incomplete information.

Error handling in pseudoLang prompts can involve:

  1. Recognizing potential issues: Identify scenarios where the AI might face difficulties, such as ambiguous input, lack of available information, or contradictory data.

  2. Providing alternative actions: When an issue is detected, offer alternative actions for the AI to take. For example, you might instruct it to ask for clarification, use a different data source, or make an educated guess based on the available information.

  3. Handling exceptions: Include steps for the AI to follow in case of unexpected situations, such as when it encounters an error while processing the data or is unable to complete a task due to insufficient information.

Here's an example of a pseudoLang prompt that incorporates error handling:

1. Define function `find_data_point(data_source: str, query: str) -> str`: 
    a. Search for the data point in the specified data source 
    b. If the data point is not found or ambiguous, return "Data not found or unclear" 

2. Define function `analyze_data_point(data_point: str) -> str`: 
    a. If the data point is "Data not found or unclear", ask for additional information or a different data source 
    b. If the data point is valid, analyze it and return the result 

3. Process: 
    a. Find a data point on "global temperature trend" using `find_data_point` from data_source "ClimateDataArchive" 
    b. Analyze the data point using `analyze_data_point` 
    c. Return the analysis result or request for more information if necessary 

In this example, the find_data_point function includes error handling to manage situations where the data is not found or is unclear. The analyze_data_point function then takes appropriate action based on the returned data.

By including error handling and exception-catching steps in your pseudoLang prompts, you can help ChatGPT navigate potential issues and generate more reliable output.

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Last updated 2 years ago