Learn How to Build a Chat GPT Project in GOlang

Table of Contents

1. Introduction
2. Building Projects with Chat GPT
3. First Project: Sending a Prompt
   1. Installing Dependencies
   2. Setting Up the Environment
   3. Creating the Client
   4. Completing the Prompt
   5. Handling Errors
4. Second Project: Chat GPT CLI Tool
   1. Configuring the Environment
   2. Creating a CLI Tool
   3. Processing User Input
   4. Quitting the Program
5. Third Project: Analyzing Code with Chat GPT
   1. Setting Up the Project
   2. Reading the Code from a File
   3. Sending the Code to Chat GPT
   4. Handling the Response
   5. Writing the Output to a File
6. Conclusion

Building Projects with Chat GPT

In today's video, we will be building three different projects using Chat GPT. Chat GPT is a powerful tool that is in high demand among developers, as many companies require expertise in chatbot development. By building these projects, You will gain valuable experience in working with Chat GPT and learn how to integrate it into your own applications.

Before we dive into the projects, let me introduce myself and explain the goals behind these tutorials. My name is [Your Name], and I specialize in teaching GoLang and Rust programming languages. I have created numerous playlists and projects on these technologies, which you can find on my YouTube Channel.

The main aim of these tutorials is to help you build real-world projects that you can showcase in your portfolio. I focus on teaching highly valuable skills that will increase your chances of landing a great job. In this video, we will be diving into the world of Chat GPT, as it is a rapidly growing field with high demand in the job market.

First Project: Sending a Prompt

To get started with our first project, we need to set up the environment and install the necessary dependencies. Once everything is configured, we can Create a client that will communicate with the Chat GPT API.

The first program we will build simply sends a prompt to the Chat GPT API and retrieves the completed response. This will give you a basic understanding of how the API works and how to Interact with it using Golang.

To begin, make sure you have the necessary API key from Chat GPT. You can find this on the Chat GPT Website after logging in. Once you have the API key, create a new Golang project and set up a go.mod file.

Inside the main.go file, import the required packages and load the API key from the environment configuration file using the go-dotenv Package.

package main

import (
    "fmt"
    "log"
    "os"

    "github.com/joho/godotenv"
    gpd3 "github.com/pullrequestinc/gpt3"
)

func main() {
    err := godotenv.Load()
    if err != nil {
        log.Fatal("Error loading .env file")
    }

    apiKey := os.Getenv("API_KEY")
    if apiKey == "" {
        log.Fatal("Missing API key. Please check your .env file.")
    }

    ctx := context.Background()
    client, err := gpd3.NewClient(ctx, apiKey)
    if err != nil {
        log.Fatal("Failed to create GPT3 client:", err)
    }

    completion, err := client.Completion.Create(ctx, &gpd3.CompletionRequest{
        Prompt:   "The first thing you should know about Golang is...",
        MaxTokens: 30,
    })
    if err != nil {
        log.Fatal("Failed to complete prompt:", err)
    }

    fmt.Println(completion.Choices[0].Text)
}

In this code, we load the API key from the environment file, create a new client with the API key, and send a completion request with a prompt to the Chat GPT API. The completed response is then printed to the console.

To run this program, make sure you have the API key stored in the .env file and execute the go run main.go command in your project directory.

Second Project: Chat GPT CLI Tool

In the second project, we will build a command-line interface (CLI) tool that interacts with Chat GPT. This tool will allow users to input Prompts and receive responses directly from the terminal.

To build this tool, we will use the Viper and Cobra packages to handle command-line arguments and environment configuration. These packages make it easy to create powerful CLI tools in GoLang.

Begin by creating a new Golang project and setting up the environment. Import the required packages, including Viper and Cobra, and create a main.go file.

package main

import (
    "context"
    "fmt"
    "log"
    "os"
    "os/signal"
    "syscall"
    "time"

    "github.com/spf13/cobra"
    "github.com/spf13/viper"
    gpd3 "github.com/pullrequestinc/gpt3"
)

var rootCmd = &cobra.Command{
    Use:   "chatgpt",
    Short: "A chatbot powered by GPT-3",
    Run: func(cmd *cobra.Command, args []string) {
        scanner := bufio.NewScanner(os.Stdin)
        quit := false

        for !quit {
            fmt.Print("Say something: ")
            scanner.Scan()
            question := scanner.Text()

            switch question {
            case "quit":
                quit = true
            default:
                getResponse(client, ctx, question)
            }
        }
    },
}

func getResponse(client *gpd3.Client, ctx context.Context, question string) {
    response, err := client.Chat.Completion(ctx, &gpd3.CompletionRequest{
        Engine:    "davinci",
        MaxTokens: 30,
        Temperature: 0.8,
        Prompt:    "Say something: " + question,
    })
    if err != nil {
        log.Fatal("Failed to get response:", err)
    }

    fmt.Println(response.Choices[0].Text)
}

In this code, we define the root command for our CLI tool using Cobra. The Run function is where the main logic of the CLI tool resides. It prompts the user to input a question, reads the input from the command line, and passes it to the getResponse function.

The getResponse function sends the question to the Chat GPT API using the client we created earlier. It then prints the response to the console.

To run this tool, make sure you have the API key stored in the .env file and execute the go run main.go command in your project directory.

Third Project: Analyzing Code with Chat GPT

In the third project, we will use Chat GPT to analyze code samples and retrieve a list of libraries used in the code. This project simulates a Scenario where you have a code file and want to extract information about the libraries used.

To get started, create a new Golang project and set up the environment. Import the required packages and create a main.go file.

package main

import (
    "context"
    "fmt"
    "io/ioutil"
    "log"
    "os"

    "github.com/joho/godotenv"
    gpd3 "github.com/pullrequestinc/gpt3"
)

func main() {
    err := godotenv.Load()
    if err != nil {
        log.Fatal("Error loading .env file")
    }

    apiKey := os.Getenv("API_KEY")
    if apiKey == "" {
        log.Fatal("Missing API key. Please check your .env file.")
    }

    ctx := context.Background()
    client, err := gpd3.NewClient(ctx, apiKey)
    if err != nil {
        log.Fatal("Failed to create GPT3 client:", err)
    }

    inputFile := "input_with_code.txt"
    outputFile := "output.txt"

    code, err := ioutil.ReadFile(inputFile)
    if err != nil {
        log.Fatalf("Failed to read file %s: %v", inputFile, err)
    }

    message := fmt.Sprintf("This is the prompt that we're going to send to Chat GPT: %s", string(code))

    completion, err := client.Completion.Create(ctx, &gpd3.CompletionRequest{
        Engine:   "davinci",
        MaxTokens: 3000,
        Temperature: 0.8,
        Prompt:    message,
    })
    if err != nil {
        log.Fatal("Failed to complete prompt:", err)
    }

    output := completion.Choices[0].Text

    err = ioutil.WriteFile(outputFile, []byte(output), 0644)
    if err != nil {
        log.Fatalf("Failed to write file %s: %v", outputFile, err)
    }
}

In this code, we load the API key from the environment file, create a new client with the API key, and Read the code file using the ioutil package. We then send the code as a prompt to the Chat GPT API and retrieve the completed response.

The completed response is written to an output file using the ioutil package.

To run this program, make sure you have the API key stored in the .env file, and you have created an input file with code samples. Execute the go run main.go command in your project directory.

Conclusion

In this video tutorial, we built three different projects using Chat GPT and explored its capabilities in various scenarios. We learned how to send prompts, create a CLI tool, and analyze code using Chat GPT.

By following along and building these projects, you have gained valuable experience in working with Chat GPT and integrating it into your own applications. Remember to always protect your API key and follow best practices when using external APIs.

Thank you for watching, and I hope you found this tutorial helpful. If you have any questions or suggestions for future videos, please feel free to leave a comment. Happy coding!

Highlights

• Build three different projects using Chat GPT
• Gain valuable experience in working with Chat GPT
• Integrate Chat GPT into your own applications
• Showcase your skills in your portfolio
• Learn highly valuable skills for job applications
• Use Viper and Cobra packages for CLI tool development
• Analyze code and retrieve information using Chat GPT

FAQ:

Q: What is Chat GPT? A: Chat GPT is a powerful language generation model developed by OpenAI. It can understand and generate human-like text responses, making it a valuable tool for chatbot development and natural language processing tasks.

Q: How can I get an API key for Chat GPT? A: You can obtain an API key for Chat GPT by signing up for an account on the OpenAI platform. Once you have an account, you can access your API key in the settings or profile section.

Q: Can I use Chat GPT for free? A: OpenAI offers a free tier for access to Chat GPT, allowing developers to experiment and build applications without incurring any costs. However, there are also paid plans available for higher usage limits and additional features.

Q: What programming languages can I use with Chat GPT? A: Chat GPT can work with various programming languages, including Golang, JavaScript, Python, Rust, and more. The choice of language depends on your preferences and the requirements of your project.

Q: Can I build a chatbot using Chat GPT? A: Yes, Chat GPT is an excellent tool for building chatbots. With its language generation capabilities, you can create chatbots that understand and respond to user queries in a conversational manner.

Q: Are there any limitations to using Chat GPT? A: While Chat GPT is a powerful tool, it does have some limitations. It may not always provide accurate or reliable responses, and it can sometimes generate biased or inappropriate content. It is crucial to review and moderate the outputs to ensure they meet the desired standards.

Q: How can I protect my API key when working with Chat GPT? A: It is essential to keep your API key secure and avoid sharing it with unauthorized individuals. One best practice is to store the API key in an environment variable or a configuration file and ensure that it is not exposed in your code or shared publicly.

Q: Can I use Chat GPT for commercial projects? A: Yes, you can use Chat GPT for commercial projects. OpenAI provides paid plans that allow for higher usage limits and commercial usage. Be sure to review the pricing and terms of service to ensure compliance with OpenAI's guidelines.