Introducing PromptAppGPT: A rapid prompt app development framework based on GPT

Hi all! We’re rolling out a rapid prompt app development framework: PromptAppGPT.

PromptAppGPT is a low-code prompt-based rapid app development framework. PromptAppGPT contains features such as low-code prompt-based development, GPT text generation, DALLE image generation, online prompt editer+compiler+runer, automatic user interface generation, support for plug-in extensions, etc. PromptAppGPT aims to enable natural language app development based on GPT.

PromptAppGPT significantly lowers the barrier to GPT application development, allowing anyone to implement their own AutoGPT-like application with 70 lines of low code.

You are wellcome to:

  1. Join us to collaboratively develop the framework
  2. Visit the website to try the framework
  3. See the example apps including the 70-line low-code implementation of the AutoGPT-like AI auto-assistant

For more information, you can search for “PromptAppGPT”.

Here is the code of the example My AutoGPT application using the PromptAppGPT framework:

author: Leo
name: My AutoGPT
description: Use gpt and executors to autonomously achieve whatever goal you set.
gptRound: multiple
failedRetries: 2
autoRun: true

  - executor: gpt
    prompt: |
      1. If you are unsure how you previously did something or want to recall past events, thinking about similar events will help you remember.
      2. No user assistance
      3. Exclusively use the commands listed in double quotes e.g. "command name"

      1. Webpage Search: "doSearchWeb", args: "query": "<keywords_to_search>"
      2. Image Search: "doSearchImage", args: "query": "<keywords_to_search>"
      3. Task Complete: "doCompleteTask", args: "output": "<task_output>"

      1. Internet access for searches and information gathering.
      2. GPT-3.5 powered Agents for delegation of simple tasks.

      Performance Evaluation:
      1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.
      2. Constructively self-criticize your big-picture behavior constantly.
      3. Reflect on past decisions and strategies to refine your approach.
      4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.

      You should only respond in JSON format as described below 
      Response Format: 
          "thoughts": {
              "text": "thought",
              "reasoning": "reasoning",
              "plan": "- short bulleted\n- list that conveys\n- long-term plan",
              "criticism": "constructive self-criticism",
              "speak": "thoughts summary to say to user"
          "command": {
              "name": "command name",
              "args": {
                  "arg name": "value"

  - trigger: doSearchWeb
    executor: bingWeb
    prompt: |
      query: $e{"query": "(.*)"}
      limit: 2
    outputer: $e{RawInput} doGptNext
  - trigger: doSearchImage
    executor: bingImage
    prompt: |
      query: $e{"query": "(.*)"}
      limit: 2
    outputer: $e{RawInput} doGptNext
  - trigger: doGptNext
    executor: gpt
    prompt: Determine which next command to use, and respond using the format specified above.
  - trigger: doCompleteTask
    executor: log
    prompt: |
       $i{Task Complete:@textarea=$e{"output": "(.*)"}}
  - executor: gpt
    prompt: |
      $i{My Objectives:@textarea=Objectives:
      1. Recommend the best smartphone for business professionals in 2023.
      2. Explain why the smartphone is recommended and show the smartphone's image.}

Here is the running results of the My AutoGPT app:

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