¡Descubre los secretos del "MemGPT" en esta clase magistral!

¡Descubre los secretos del "MemGPT" en esta clase magistral!

Table of Contents

1. Introduction
2. Overview of the MGPT Code Base
3. Running MGPT as a Discord Bot
4. MGPT CLI Setup and Basic Chat Demo
5. Using MGPT to Chat with Documents
6. Running MGPT with Local LLMS without OpenAI
7. Adding Custom Functions to MGPT
8. Memory Function in MGPT
9. Setting Up MGPT as a Discord Bot
10. Running MGPT on the Command Line
11. Running MGPT with Local Language Models

Introduction

In this MGPT crash course, You will learn from the Creators of MGPT, Vivian and Charles, on five important topics. This course will provide you with a brief overview of the MGPT code base, guide you through the easiest way to run MGPT as a Discord bot, help you set up MGPT CLI and provide a basic chat demo, Show you how to use MGPT to chat with documents, and teach you how to run MGPT with local LLMS without OpenAI. You will also learn how to add custom functions to MGPT and understand how the memory function works in MGPT. Lastly, we will discuss setting up MGPT as a Discord bot and running MGPT on the command line. Let's dive in!

Overview of the MGPT Code Base

The MGPT code base is primarily located in the agent.py file. Inside the asynchronous agent, the step function is called each time a user sends a message. The user message is appended to the internal message queue, and then it is sent to the OpenAI API or a local language funnel API for a response. The response, which is the assistant's reply, is obtained by passing the messages to the language model. Additionally, you can add your own functions to MGPT by updating the available functions bank. To demonstrate this, we have a function called messageChatGPT that allows MGPT to call ChatGPT or GPT-3.5 to answer questions. Adding this function requires making a few changes in the agent class itself. This includes calling the messageChatGPT function and providing a concatenated STRING for the message. Overall, the MGPT code base is modular and allows for easy customization.

Running MGPT as a Discord Bot

The easiest way to get started with MGPT is by running it as a Discord bot. This method does not require you to install or download any code. Simply use your Discord account and obtain an OpenAI API Key. Begin by setting up a user profile for MGPT, where you can provide personal information about yourself. This information is used to seed the bot. Next, link your OpenAI API key to the bot. Adjust your privacy settings to allow direct messages from other members in the server. Once these steps are complete, you can Create a bot with default personas or create your own. MGPT will confirm the successful creation of your AI Chatbot, and you can begin chatting with it in a direct message.

MGPT CLI Setup and Basic Chat Demo

To run MGPT on the command line interface (CLI), you first need to install the pymgpt Package. Once installed, you can configure MGPT to use the desired language model, such as gp4, and specify a user profile and persona. With the CLI setup complete, you can now start chatting with MGPT. You can correct MGPT if it mentions your name incorrectly, and it will update its internal memory accordingly. Exiting the chat session will save a transcript of the conversation. When you run MGPT again, you can load the saved transcript, ensuring that MGPT remembers the correct name. The CLI setup allows for easy integration and management of conversations with MGPT.

Using MGPT to Chat with Documents

MGPT can be used to chat with documents, allowing you to leverage its language abilities to extract information. By using the doc command, you can specify a document or a folder of documents to be loaded into MGPT's archival memory. Once loaded, you can ask MGPT questions related to the content in the documents. MGPT will query its archival memory to provide answers Based on the information in the documents. This feature allows you to effectively Interact with knowledge stored within the documents and obtain Relevant information in a conversational manner.

Running MGPT with Local LLMS without OpenAI

If you prefer to run MGPT with local language models instead of relying on the OpenAI API, you can do so by hosting the models on your own web server. This method allows for more control and privacy. By using a web user interface (webUI) like Texar, you can load and configure the desired language model. To use local language models with MGPT, you need to set the OPENAI_API_BASE variable to the location of your web server and specify the backend_type as webUI. This will instruct MGPT to communicate with the local language models instead of OpenAI. These local language models provide a more lightweight option for using MGPT.

Adding Custom Functions to MGPT

MGPT provides the flexibility to add custom functions and extend its capabilities. To add a new function, you need to update the available functions bank. This can be done by modifying the code in a few places. By creating a new function and specifying its behavior, you can expand the functionality of MGPT. For example, you can enable MGPT to write to a Word document by adding a new function that handles this task. The customization possibilities are extensive, allowing you to tailor MGPT to suit your specific requirements and integrate it with other tools or systems.

Memory Function in MGPT

Memory in MGPT is held inside Python objects and can be persisted by saving it to a file. However, if you want to implement a database for memory storage instead, you can create a new archival memory subclass or a new recall memory subclass. Depending on which memory component you want to replace or enhance, you can implement specific code for inserting and searching records in your database. To use these new memory classes, you need to instantiate them when creating a new instance of MGPT and update the persistence manager accordingly. This allows you to seamlessly switch between different memory storage mechanisms based on your needs.

Setting Up MGPT as a Discord Bot

To set up MGPT as a Discord bot, you need to follow a few steps. Begin by creating a user profile for the bot, providing relevant information about yourself. Then, link your OpenAI API key to enable the bot to fetch responses from the OpenAI API. Adjust your privacy settings to allow direct messages from other members in the server. Once these settings are configured, you can create a bot and select the desired profile and persona. MGPT will guide you through the creation process and confirm the successful creation of your AI chatbot. Afterward, you can start interacting with the bot in a direct message.

Running MGPT on the Command Line

MGPT can also be run on the command line interface (CLI). To run MGPT on the CLI, you need to install the pymgpt package. With the package installed, you can configure MGPT to use the desired language model and user profile. Once configured, you can interact with MGPT through text input on the command line. MGPT will process your input and generate responses based on the language model and memory it has access to. This allows for more flexibility and control when using MGPT for various applications.

Running MGPT with Local Language Models

In addition to using the OpenAI API, MGPT provides the option to run with local language models. By hosting the models on a web server, you can reduce dependence on external APIs and have more control over the deployment. To run MGPT with local language models, you need to specify the appropriate API base and backend Type in the configuration. This will allow MGPT to interact with the locally hosted models instead of routing requests to the OpenAI API. Running MGPT with local language models offers greater customization and privacy while still benefiting from the powerful language capabilities of MGPT.

Pros

• Easy integration with Discord for real-time chatbot interactions.
• Customizable functions to extend MGPT's capabilities.
• Support for loading and querying documents for conversational access to information.
• Flexibility to run MGPT with local language models for increased control and privacy.
• Ability to persist and retrieve memory using both file-based and database-based storage.

Cons

• Initial setup and configuration may require some technical knowledge.
• Customizing MGPT with new functions or memory storage mechanisms may require familiarity with Python programming.
• Hosting and managing local language models can be resource-intensive and may require advanced infrastructure setup.

FAQ:

Q: Can I use MGPT to write to a Word document? A: Yes, you can add a custom function to MGPT that enables it to write to a Word document. By modifying the code in a few places, you can extend MGPT's functionality to include this capability.

Q: How does memory storage work in MGPT? A: Memory in MGPT is held inside Python objects and can be persisted as a file. However, you can also implement a database to store memory records. By creating a new memory subclass and updating the persistence manager, you can customize MGPT's memory storage mechanism.

Q: Can I run MGPT as a Discord bot without downloading any code? A: Yes, you can run MGPT as a Discord bot without installing or downloading any code. Simply create a user profile, link your OpenAI API key, and set up the bot using the provided instructions.