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Conditional Prompts

Conditional prompting uses branching logic or dynamic prompt construction, allowing the language model to adapt its responses based on specific conditions or user inputs. This technique is essential for building flexible, context-aware, and interactive AI systems.

Key Concepts​

  • Branching Logic: The prompt or workflow changes based on user input or model output.
  • Dynamic Prompting: Prompts are constructed or modified in real time according to conditions.
  • Context Sensitivity: The model adapts to the current context, preferences, or requirements.
  • Personalization: Responses are tailored to individual users or scenarios.

Best Practices​

  1. Define Clear Conditions

    • Specify the criteria for branching or adapting the prompt.
    • Use explicit if-then logic or rules.

  2. Structure Prompts for Flexibility

    • Design prompts to accommodate multiple paths or outcomes.
    • Use templates or modular components.

  3. Test All Branches

    • Validate that each condition leads to the correct prompt and output.
    • Check for edge cases and unexpected inputs.

  4. Maintain Context

    • Pass relevant information between branches or steps.
    • Ensure continuity across dynamic changes.

Examples​

Basic Conditional Prompt​

If the user asks for a joke, tell a joke.
If the user asks for a fact, provide an interesting fact.

User: "Tell me a joke."
Assistant: "Why did the scarecrow win an award? Because he was outstanding in his field!"

Dynamic Prompt Construction​

If the user is a beginner, explain the concept simply.
If the user is advanced, provide a technical explanation.

User: "Explain recursion." (user_level: beginner)
Assistant: "Recursion is when a function calls itself to solve a problem step by step."

User: "Explain recursion." (user_level: advanced)
Assistant: "Recursion is a method where the solution to a problem depends on solutions to smaller instances of the same problem, often implemented via self-referential function calls."

Multi-step Workflow​

If the user's request is unclear, ask a clarifying question.
If the request is clear, proceed with the task.

User: "Book a flight."
Assistant: "Where would you like to fly to, and on what date?"

Personalized Recommendations​

If the user prefers vegetarian food, suggest vegetarian recipes.
If not, suggest popular dishes.

User: "What should I cook for dinner?" (preference: vegetarian)
Assistant: "How about a delicious vegetable stir-fry or a lentil soup?"

Common Pitfalls​

  1. Unclear or Overlapping Conditions

    • Ambiguous rules lead to unpredictable behavior.
    • Multiple conditions match the same input.

  2. Incomplete Branch Coverage

    • Not handling all possible user inputs or scenarios.
    • Missing default or fallback branches.

  3. Loss of Context

    • Failing to pass necessary information between branches.
    • Forgetting user preferences or previous choices.

  4. Complexity Overload

    • Too many branches make the system hard to manage.
    • Increased risk of errors and inconsistencies.

Use Cases​

  1. Conversational Agents

    • Adaptive dialogue flows
    • Clarification and disambiguation

  2. Personalization

    • Tailored recommendations
    • User-specific content

  3. Task Automation

    • Multi-step workflows
    • Conditional task execution

  4. Interactive Applications

    • Games and simulations
    • Educational tools

When to Use Conditional Prompts​

Conditional prompting is ideal when:

  • The task requires adaptation to user input or context.
  • Multiple outcomes or paths are possible.
  • Personalization or context-awareness is important.
  • The system must handle ambiguity or incomplete information.

When to Consider Alternatives​

Consider other techniques when:

  • The task is simple and does not require branching.
  • All users or scenarios can be handled with a single prompt.
  • Complexity outweighs the benefits of flexibility.

Tips for Optimization​

  1. Modular Design

    • Build prompts as reusable components.
    • Make it easy to add, remove, or update branches.

  2. Clear Documentation

    • Document all conditions and branches.
    • Use flowcharts or diagrams for complex logic.

  3. Iterative Testing

    • Test all branches and edge cases.
    • Refine conditions based on user feedback.

  4. Fallback Handling

    • Include default responses for unhandled cases.
    • Gracefully handle unexpected inputs.