AI Prompt Engineering is a Streamlit app that allows users to experiment with different types of prompts for AI language models. The app provides a user-friendly interface for entering text or code and generating summarized or cleaned output.
The app is available at http://prompteng.streamlit.app.
AI language models are powerful tools that can generate human-like text and perform a wide range of natural language processing tasks. These models are trained on large amounts of text data and can generate coherent and fluent responses to a wide range of prompts.
However, the quality of the output generated by an AI language model depends heavily on the quality of the prompt provided to the model. A well-crafted prompt can elicit a highly relevant and informative response from the model, while a poorly-crafted prompt can result in irrelevant or nonsensical output.
Providing clear and informative prompts to an AI language model is essential for achieving the best results. A good prompt should be specific, concise, and unambiguous. It should provide enough context for the model to understand the task at hand and generate a relevant response.
In addition to being clear and informative, a good prompt should also be engaging and thought-provoking. It should encourage the model to generate creative and insightful responses that provide value to the user.
Large language models (LLMs) have a fixed token size limit, which means that they can only process a certain number of tokens at a time. This limit varies depending on the specific model, but it is typically in the range of several hundred to several thousand tokens.
When providing a prompt to an LLM, it is important to keep this token size limit in mind. If the prompt exceeds the token size limit of the model, it will be truncated and only the first part of the prompt will be processed by the model. This can result in incomplete or irrelevant output.
To avoid exceeding the token size limit of an LLM, it is recommended to keep prompts concise and focused. If you need to provide a large amount of information in your prompt, consider breaking it up into smaller chunks and providing them to the model one at a time.
AI Prompt Engineering makes it easy to experiment with different types of prompts for AI language models. The app provides two main features: Text and Code.
In the Text section, users can enter a block of text and generate a summarized version of the text using the Sumy library. The summarized text is displayed in the app along with information about the output token size.
In the Code section, users can enter Python code and generate a cleaned version of the code that removes all annotations (i.e., comments starting with "#"). The cleaned code is displayed in the app along with information about the output token size.
Both sections also provide a "Copy to clipboard" button that allows users to easily copy the summarized text or cleaned code to their clipboard.
We hope that AI Prompt Engineering will be a useful tool for anyone looking to experiment with different types of prompts for AI language models. Give it a try at http://prompteng.streamlit.app!
This project is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.