Create AI Text Summarizer with OpenAI GPT-3 | No-Code Tutorial

Table of Contents

1. Introduction
2. Building a Test Summarizer App with Mountain
3. Setting Up the Environment
4. Creating the Prompt
5. Parameter Settings
6. Testing the Application
7. Deploying the Application
8. Conclusion
9. Additional Resources

Introduction

In this tutorial, we will walk You through the process of building a test summarizer app using the Mountain no-code platform. We will be using the OpenAI GPT-3 model to Create this app. This tutorial is designed to be beginner-friendly and will provide step-by-step instructions on how to set up the environment, create the prompt, configure the parameter settings, test the application, and finally, deploy the app.

Building a Test Summarizer App with Mountain

To get started, make sure you have access to the Mountain local platform. Navigate to app.manciumai.com on your browser and sign in to your account. If you don't have an account, you can create one for free. Once logged in, ensure that the OpenAI API Key is connected to the Mountain app. This is necessary as we will be using the OpenAI GPT-3 model for the text summarizer app. If you haven't connected the API key yet, follow the instructions provided on the AI Provider page to connect it.

Setting Up the Environment

Before we can start building the prompt for our text summarizer app, we need to set up the environment. Within the AI Manager tab, click on "Add a New Prompt" to begin creating our prompt. This will open a new window where we can provide details, parameter settings, and the prompt text.

Creating the Prompt

The first step in creating the prompt is to give it a name and description. These details will help us recognize the prompt easily. You can choose to provide your own name and description, but for this tutorial, we will use "AI Text Summarizer" as the name.

The prompt text is the body of our prompt and should contain examples of complex paragraphs and their corresponding summaries. We want the model to take a complex paragraph and generate a summary. It is recommended to use a few-shot learning approach, where we provide multiple examples for the model to learn from.

Parameter Settings

Next, we need to configure the parameter settings for our application. This involves choosing a provider, endpoint, and model. Since We Are working with the OpenAI GPT-3 model, we will select the "OpenAI" model and the "Davinci" endpoint. The response length parameter determines the length of the response we get from the model. For this tutorial, we will set the response length to 20000.

The temperature value is used to control the creativity of the response. A value closer to 1 will result in more creative responses, while a value closer to 0 will produce less creative responses. For this use case, we will set the temperature value to 0.6, aiming for a balance between creativity and coherence.

Testing the Application

Once the prompt and parameter settings are configured, we can test the application. Enter a complex Paragraph as input and run the application to get a summarized version of the text. You can find an example input in the description below. Keep in mind that due to the stochastic nature of natural language models, you may receive different results each time you run the prompt.

Deploying the Application

Once you are satisfied with the testing, it's time to deploy the application. Click on the "Deploy" button in the top right corner of the Mountain platform. Provide the necessary details, including the name, description, and author name. Make sure to check the "Add Input Field" option and select the "Public" life option. By following these steps, the Mountain platform will create a single-page web application for your text summarizer app.

Conclusion

In this tutorial, we have learned how to build a text summarizer app using the Mountain no-code platform and the OpenAI GPT-3 model. We covered the steps from setting up the environment to deploying the application. Now you can share the single-page web application with others and allow them to test the app by providing a body of text and receiving its summary. If you need any assistance or further guidance, feel free to join our Discord community.

Additional Resources

• OpenAI GPT-3
• Mountain No-Code Platform
• Prompt Learning Approach
• Mountain Discord Community

Test Summarizer App with Mountain: Simplifying the Task of Summarizing Texts

Welcome to this tutorial on how to build a text summarizer app using the Mountain no-code platform. In this step-by-step guide, we will Show you how to leverage the power of the OpenAI GPT-3 model to create an application that can generate summaries of complex paragraphs. Whether you're a beginner or an experienced developer, this tutorial will provide you with all the necessary instructions to create your own text summarizer app.

Introduction

Summarizing a lengthy text can be a daunting task, especially when dealing with complex content. However, with the help of modern AI models, we can automate this process and achieve accurate and concise summaries. In this tutorial, we will utilize the Mountain no-code platform to simplify the development process and demonstrate how the OpenAI GPT-3 model can be used to build a text summarizer app.

Building a Test Summarizer App with Mountain

To get started, make sure you have access to the Mountain local platform. If you don't have an account yet, visit app.manciumai.com and create one. Once logged in, navigate to the AI Manager tab and click on "Add a New Prompt." This will open a prompt creation window where you can define the parameters of your text summarizer app.

Setting Up the Environment

The first step in building any application is to set up the environment. In this case, we need to ensure that our OpenAI API key is connected to the Mountain app. This will allow us to utilize the power of the OpenAI GPT-3 model. If you haven't connected your API key yet, simply navigate to the AI Provider tab and follow the instructions to connect it.

Creating the Prompt

The prompt is the Core component of our text summarizer app. It contains examples of complex paragraphs and their corresponding summaries, serving as a guide for the model to learn from. When creating your prompt, make sure to provide multiple examples for a more effective few-shot learning approach.

Parameter Settings

Before we can test our application, we need to configure the parameter settings. These settings determine the behavior of the OpenAI GPT-3 model. For our text summarizer app, we will choose the "OpenAI" model and the "Davinci" endpoint. We will also set the response length to 20000 and the temperature value to 0.6, striking a balance between creativity and coherence.

Testing the Application

With the prompt and parameter settings in place, it's time to test our text summarizer app. Enter a complex paragraph as input and run the application to generate a summarized version of the text. It's important to note that due to the stochastic nature of language models, the results may vary slightly with each execution.

Deploying the Application

Once you are satisfied with the testing phase, it's time to deploy your text summarizer app. Mountain provides a seamless deployment process that creates a single-page web application for you. Simply click on the "Deploy" button in the top right corner of the platform and provide the necessary details. This will generate a web app that can be shared with others for testing and feedback.

Conclusion

In this tutorial, we have explored the process of building a text summarizer app using the Mountain no-code platform and the OpenAI GPT-3 model. We have covered everything from setting up the environment to deploying the application. By following this guide, you can create your own text summarizer app and simplify the task of generating summaries for complex paragraphs.