Create Your Own Unique GPT Bot

Table of Contents

1. Introduction
2. Setting Up the Development Environment
3. Customizing a Bot with Personality
4. Deploying the Bot to the Web
5. Connecting to the Bot from Telegram
6. Running the Bot in the Console
7. Adding Tools to the Bot
8. Prompt Injection for the Personality
9. Configuring Different LLMs
10. Deploying the Bot with Steamship

Article

Introduction

In this article, we will discuss how to customize a bot with a personality, deploy it to the web, and connect to it from Telegram. We will walk you through a hackathon that took place at Harvard and demonstrate the steps to achieve these goals.

Setting Up the Development Environment

To get started, visit steamship.com/hackathon-harvard and click on the starter project. This will redirect you to Replit, where you can fork a template and have everything you need to customize and deploy a bot with Steamship. Alternatively, you can develop in VS Code, on localhost, GitHub Cloud, or other platforms.

Customizing a Bot with Personality

In the source api.py file, you will find a base class for an agent that allows you to add tools and customize the bot's personality. For now, let's focus on the personality, which is essentially a prompt injection added to the prompt passed to the language model (GPT-3 or GPT-4). You can configure the backend to use different language models.

Prompt Engineering

Running the bot with a prompt like "Hi, how's it going?" will generate a response from the bot, ideally in the style of a pirate. However, you can change the prompt to simulate the voice of a NASA mission control operator or any other character. Experimenting with different prompts and prompt engineering will improve the bot's responses.

Deploying the Bot to the Web

To deploy the bot to the web, you need to follow a slightly different process. When you deploy your bot, you are essentially deploying a cloud SaaS that others can create instances of. This means that the deployment process sits between you and using your own instance. To begin the deployment process, stop your bot and open the shell.

Adding Steamship API Key

As the deployment process requires your Steamship API key, go to steamship.com/account/API and copy your API key to the clipboard. Then, go back to Replit, navigate to "Secrets," and add a new secret called "steamship API key." Paste your API key in the value field and click "Add New Secret." Close the secrets tab and the shell.

Connecting to the Bot from Telegram

To connect to your bot from Telegram, you need to follow a few steps. Start by running the deployment script by typing python deploy.py in the shell. This script assists with the deployment process and will prompt you to enter a handle for your package. Make sure to name your package ending in "-bot" to get access to a special web interface.

Running the Bot in the Console

With the deployment complete, you can run your bot in the console. However, keep in mind that this console version does not have any tools connected to it. Try initiating a conversation by saying "Hi, how's it going?" to see if the prompt injection is working. The bot should respond based on the personality you assigned.

Adding Tools to the Bot

The base class for the agent allows you to add tools and customize your bot further. By connecting tools and adding custom data, you can make your bot specific to your needs. Steamship provides features like a vector store, S3-like blob storage, and tool storage. These capabilities enable you to enhance the functionality and uniqueness of your bot.

Prompt Injection for the Personality

The prompt injection technique is crucial for shaping the bot's personality and responses. By engineering the prompts, you can steer the conversation in a specific direction, making it more engaging and authentic. Remember that prompt engineering requires experimentation and refinement to achieve the desired results.

Configuring Different LLMs

Steamship allows you to configure various language models (LLMs) in the backend. This flexibility enables you to leverage different LLMs based on your requirements and preferences. Experiment with different models to find the one that best fits your bot's personality and ensures accurate and contextually appropriate responses.

Deploying the Bot with Steamship

To deploy your custom bot with Steamship, you need to follow the deployment process explained earlier. By naming your package ending in "-bot," you gain access to a user-friendly web interface that allows you to communicate with your bot, view logs, and add more monitoring capabilities. Using the provided URLs, you can enable others to access your bot through an API or connect it to various platforms like Telegram.

Conclusion

In this article, we explored the process of customizing a bot with a personality, deploying it to the web, and connecting to it from Telegram. We discussed prompt injection techniques, adding tools, and configuring different language models. With Steamship, you can create your own customized bot, enhancing its personality and functionality. Get started today and share your creations with the Steamship community!

Highlights

• Customize a bot with a unique personality
• Deploy the bot to the web and connect it to Telegram
• Use prompt injection to shape the bot's responses
• Add tools and custom data to make the bot specific to your needs
• Configure different language models for improved performance

FAQ

Q: Can I develop the bot in a different environment other than Replit? A: Yes, you can develop the bot in VS Code, on localhost, or other platforms. Replit is just one option provided for convenience.

Q: Is prompt engineering necessary for the bot's personality? A: Prompt engineering is crucial for shaping the bot's personality and achieving desired responses. Experimentation and refinement are essential for optimal results.

Q: Can I connect tools and store files with Steamship? A: Yes, Steamship provides features like a vector store, blob storage, and tool storage, allowing you to enhance your bot's functionality and store relevant data.

Q: Can I deploy my bot with Steamship to platforms other than Telegram? A: Currently, Steamship supports connection to Telegram. However, the platform aims to expand its support for other transports like Slack or WhatsApp in the future.

Q: How can I monitor the usage and performance of my bot's service? A: Steamship offers monitoring capabilities that allow you to track service usage across different language models and generative services associated with your bot.