Special care with tools and actions
Posted: Sun Feb 02, 2025 3:55 am
Consistency and clarity
Explicitly define terms and expectations you use using few-shot prompting (e.g., acceptable vs. unacceptable changes) to improve consistency in assessments. Clarify all relevant classifications using few-shot examples to reduce variability in output. Consistency and clarity are critical for reliable results.
2.1 Use of knowledge files
Provide explicit instructions on how to use knowledge files, including specifying file names. Instruct the model to take its time and analyze the entire file to ensure comprehensive use. Careful inclusion of knowledge files can significantly improve the quality of results.
2.2 Specificity in prompts for knowledge extraction
Increase specificity in prompts, especially when extracting turkey number dataset critical information such as dates or financial information. Give specific examples through few-shot prompting. Encourage the model to thoroughly check its work and take its time when retrieving specific data from files. Precise prompts produce more accurate results.
2.3 Examples of good expenses
Provide examples of good outputs in terms of knowledge and custom actions. These examples will guide the model and help it understand and produce the desired output. The clearer your expectations are communicated, the better the results will be.
2.4 Referencing Actions
Always reference actions by name and domain to increase clarity. Provide few-shot prompting examples with API calls where needed to ensure the correct action is called. Use separators for different action steps to ensure the correct actions are called. Accurate referencing of actions is critical for correct execution.
2.5 Explicit instructions for using tools
Provide explicit instructions on how to use tools like Browse, Knowledge, and Custom Actions in the instructions. By directly instructing the model to use these tools, you ensure that it makes the best use of all available resources to achieve the best possible results.
Conclusion: The path to optimal custom GPTs
Following these guidelines is key to optimizing the performance of your custom GPTs and ensuring reliable and accurate results. Through effective prompt engineering, clear instructions, and careful use of tools and actions, you can unlock the full potential of your AI models. Invest some time in building your own GPTs, and the investment will usually pay off in the long run.
Explicitly define terms and expectations you use using few-shot prompting (e.g., acceptable vs. unacceptable changes) to improve consistency in assessments. Clarify all relevant classifications using few-shot examples to reduce variability in output. Consistency and clarity are critical for reliable results.
2.1 Use of knowledge files
Provide explicit instructions on how to use knowledge files, including specifying file names. Instruct the model to take its time and analyze the entire file to ensure comprehensive use. Careful inclusion of knowledge files can significantly improve the quality of results.
2.2 Specificity in prompts for knowledge extraction
Increase specificity in prompts, especially when extracting turkey number dataset critical information such as dates or financial information. Give specific examples through few-shot prompting. Encourage the model to thoroughly check its work and take its time when retrieving specific data from files. Precise prompts produce more accurate results.
2.3 Examples of good expenses
Provide examples of good outputs in terms of knowledge and custom actions. These examples will guide the model and help it understand and produce the desired output. The clearer your expectations are communicated, the better the results will be.
2.4 Referencing Actions
Always reference actions by name and domain to increase clarity. Provide few-shot prompting examples with API calls where needed to ensure the correct action is called. Use separators for different action steps to ensure the correct actions are called. Accurate referencing of actions is critical for correct execution.
2.5 Explicit instructions for using tools
Provide explicit instructions on how to use tools like Browse, Knowledge, and Custom Actions in the instructions. By directly instructing the model to use these tools, you ensure that it makes the best use of all available resources to achieve the best possible results.
Conclusion: The path to optimal custom GPTs
Following these guidelines is key to optimizing the performance of your custom GPTs and ensuring reliable and accurate results. Through effective prompt engineering, clear instructions, and careful use of tools and actions, you can unlock the full potential of your AI models. Invest some time in building your own GPTs, and the investment will usually pay off in the long run.