Enhance all your Prompts for Free, Increase Productivity and Gen AI App Effectiveness 10-Fold in under 10 seconds.

Abish Pius
4 min readJun 3, 2023
“Dog in a Cup”, Stable Diffusion Prompt Enhanced via Auto Prompt Engineer

By now, I am sure the app development world is fully invested in the massive craze generated by the Generative Ai tools like ChatGPT, BARD and Midjourney. It provides both new developers and seasoned veterans the opportunity to bring their ideas to life quickly and efficiently.

Today, I have a tool that is intended to enhance this process even further by improving the prompt passed into Gen AI models. And the best part … it is fully FREE to take advantage of here: Personal Prompt Engineer

Introducing a Personal Prompt Engineer

Using Auto Prompt Engineer

Auto Prompt Engineer — Web Interface

The tool is hosted through the HuggingFace platform and can be accessed completely for free. Auto Prompt Engineer (APE) is designed to take in a prompt for any Generative AI model and enhance it for use in building custom apps for any field.

For example, lets say you want to build an LLM (Large Language Model) specifically for assisting students with algebra questions. And the prompt you have come up with is “Assistant is designed to do high school alegbra problems on a step by step basis”. You can input this prompt and BOOM! In under 10 seconds you have a prompt that is gaurenteed to be much better at producing the intended result.

Example of use case

What is a Prompt?

When it comes to large language models, prompts are the input text or instruction that serves as a guide for generating output. They can range from a single sentence to a longer passage, and they provide the initial context and direction for the AI model to follow. Prompts act as cues, shaping the AI’s response and influencing the output’s style, tone, and content.

Prompts play a crucial role in guiding the output of large language models. By carefully crafting a prompt, you can steer the AI towards generating text that aligns with your desired outcome. For example, a prompt can be used to ask a question, provide specific instructions, or set the tone for a creative piece. The language model then uses the prompt as a starting point to generate a coherent and contextually relevant response.

Here are some examples of prompts that can be used with large language models:

Generating text:

  • “Write me a poem about love.”
  • “Write me a code that will print the Fibonacci sequence.”
  • “Write me a script for a short film.”
  • “Write me a musical piece in the style of Mozart.”
  • “Write me an email to your boss asking for a raise.”

Translating languages:

  • “Translate this sentence from English to French.”
  • “Translate this paragraph from Spanish to German.”
  • “Translate this book from Chinese to English.”

Writing different kinds of creative content:

  • “Write me a short story about a robot who falls in love with a human.”
  • “Write me a poem about the beauty of nature.”
  • “Write me a script for a comedy sketch.”

Answering your questions in an informative way:

  • “What is the capital of France?”
  • “Who was the first president of the United States?”
  • “What is the meaning of life?”

Prompts are a powerful tool that can be used to control the output of large language models. By using prompts, you can generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way.

How to use as an API endpoint

We are basically at the stage where thinking is time waste as a developer. Let the machine think for you by fully integrating APE through its API call, which is also fully FREE!

Usage in Python

# Install if Needed
!pip install gradio_client

from gradio_client import Client

# Set up Endpoint connection
client = Client("https://piusanalytics-personal-prompt-engineer.hf.space/")

def call_APE(prompt):
result = client.predict(
prompt, # str in 'Enter your Prompt' Textbox component
api_name="/predict"
)
return result

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Abish Pius

Data Science Professional, Python Enthusiast, turned LLM Engineer