by we

Web3Chat

Test this app for free
49
import logging

from flask import Flask, render_template
from gunicorn.app.base import BaseApplication

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

app = Flask(__name__)


@app.route("/")
def home_route():
    return render_template("home.html")


class StandaloneApplication(BaseApplication):
    def __init__(self, app, options=None):
        self.application = app
        self.options = options or {}
        super().__init__()

    def load_config(self):
        config = {
Get full code

Frequently Asked Questions

What is Web3Chat and how can it benefit businesses?

Web3Chat is a secure messaging application that leverages Web3 technology and Metamask for user authentication. It offers businesses a unique way to communicate with clients or team members while ensuring message integrity through blockchain-based signing. The added feature of AI-generated signing certificates provides an extra layer of verification, which can be particularly valuable for industries dealing with sensitive information or requiring high levels of trust in communications.

How does Web3Chat's AI-generated signing certificate feature work?

When a user sends a message in Web3Chat, the application first signs the message using the user's Metamask wallet. Then, it utilizes an AI model (GPT-4 in this case) to generate a signing certificate for the message. This certificate serves as an additional verification layer, potentially including details about the message content, timestamp, and signature. Here's a code snippet demonstrating this process:

javascript sendMessageButton.addEventListener('click', async () => { const message = messageInput.value; const signedMessage = await signMessage(message); const aiGeneratedMessage = await llm_prompt(`Generate a signing certificate for the message: "${message}" signed as: "${signedMessage}"`, "gpt-4-1106-preview", 0.7); console.log("AI Generated Signing Certificate:", aiGeneratedMessage); });

What industries or use cases would benefit most from implementing Web3Chat?

Web3Chat would be particularly beneficial for industries that require secure, verifiable communications. Some examples include: - Legal services: For secure client-attorney communications - Financial services: For verified transactions and sensitive financial discussions - Healthcare: For secure patient-doctor communications compliant with privacy regulations - Government agencies: For secure inter-departmental communications - Intellectual property: For securely sharing and discussing confidential ideas or designs

How does Web3Chat handle user authentication?

Web3Chat uses Metamask for user authentication, leveraging the power of blockchain technology. When a user clicks the "Login with MetaMask" button, the application initiates a connection with the user's Metamask wallet. Here's the relevant code snippet:

javascript async function initWeb3() { if (typeof window.ethereum !== 'undefined') { try { await window.ethereum.request({ method: 'eth_requestAccounts' }); window.web3 = new Web3(window.ethereum); return true; } catch (error) { console.error("User denied account access", error); return false; } } else { console.error("MetaMask is not installed!"); return false; } }

This method ensures that only users with valid Ethereum wallets can access the chat, providing a secure and decentralized authentication mechanism.

Can Web3Chat be integrated with existing business communication systems?

While the current template for Web3Chat is a standalone application, its modular design using Flask and JavaScript makes it highly adaptable. Businesses could potentially integrate Web3Chat's secure messaging and AI-generated signing certificate features into their existing communication systems. This would require some custom development, but the core functionalities provided in the template serve as a solid foundation for such integrations, allowing businesses to enhance their current systems with Web3 and AI capabilities.

Created: | Last Updated:

Web3Chat: A chat app that utilizes Metamask for secure messaging and AI-generated sign messages. No environment variables required. Discord members needs a friend request from <@1240703821093671002> before using

Here's a step-by-step guide on how to use the Web3ChatApp template:

Introduction to the Web3ChatApp Template

The Web3ChatApp template provides a foundation for building a chat application that integrates with MetaMask for secure messaging and uses AI to generate signing certificates. This app allows users to log in with MetaMask, send messages, and receive AI-generated signing certificates for their messages.

Getting Started

To begin using this template, follow these steps:

  1. Click "Start with this Template" in the Lazy Builder interface.
  2. Press the "Test" button to deploy the app and launch the Lazy CLI.

Using the Web3ChatApp

Once the app is deployed, you can access it through the dedicated server link provided by Lazy. Here's how to use the app:

  1. Open the app in your web browser.
  2. Click the "Login with MetaMask" button.
  3. If prompted, connect your MetaMask wallet to the app.
  4. Once connected, the chat interface will appear.
  5. Type your message in the text area.
  6. Click the "Send Message" button.

The app will then: - Sign your message using MetaMask - Generate an AI signing certificate for the message - Log the AI-generated signing certificate to the console (in a production app, you would typically send this to a server or display it in the UI)

Integrating MetaMask

To use this app, users will need to have the MetaMask browser extension installed. Here are the steps for users to set up MetaMask:

  1. Install the MetaMask extension for their browser from metamask.io.
  2. Create a new MetaMask wallet or import an existing one.
  3. Connect MetaMask to the Ethereum network of their choice (MainNet, TestNet, etc.).

Customizing the App

To customize the app for your specific needs, you may want to modify the following parts of the code:

  1. Update the HTML in home.html to change the app's appearance.
  2. Modify the script.js file to add new functionality or change how messages are processed.
  3. Adjust the main.py file if you need to add new routes or server-side functionality.

Next Steps

To further develop this app, consider implementing the following features:

  • Store messages and signing certificates in a database.
  • Create a backend API to handle message storage and retrieval.
  • Implement a real-time chat feature using WebSockets.
  • Add user authentication and account management.

Remember that all deployment and hosting is handled by Lazy, so you don't need to worry about server setup or environment configuration.



Here are 5 key business benefits for the Web3Chat template:

Template Benefits

  1. Enhanced Security: Leverages Web3 and MetaMask for secure user authentication, ensuring only authorized users can access the chat application.

  2. Blockchain Integration: Demonstrates practical implementation of blockchain technology in a messaging app, opening doors for cryptocurrency-related features or token-gated access.

  3. AI-Powered Verification: Utilizes AI to generate signing certificates for messages, adding an extra layer of authenticity and potentially reducing fraud or impersonation.

  4. Scalable Architecture: Built with Flask and Gunicorn, providing a robust and scalable foundation for handling multiple concurrent users.

  5. Cross-Platform Compatibility: Web-based interface allows for easy access across different devices and operating systems, increasing potential user base and adoption.

Technologies

Maximize OpenAI Potential with Lazy AI: Automate Integrations, Enhance Customer Support and More  Maximize OpenAI Potential with Lazy AI: Automate Integrations, Enhance Customer Support and More
Streamline JavaScript Workflows with Lazy AI: Automate Development, Debugging, API Integration and More  Streamline JavaScript Workflows with Lazy AI: Automate Development, Debugging, API Integration and More

Similar templates

FastAPI endpoint for Text Classification using OpenAI GPT 4

This API will classify incoming text items into categories using the Open AI's GPT 4 model. If the model is unsure about the category of a text item, it will respond with an empty string. The categories are parameters that the API endpoint accepts. The GPT 4 model will classify the items on its own with a prompt like this: "Classify the following item {item} into one of these categories {categories}". There is no maximum number of categories a text item can belong to in the multiple categories classification. The API will use the llm_prompt ability to ask the LLM to classify the item and respond with the category. The API will take the LLM's response as is and will not handle situations where the model identifies multiple categories for a text item in the single category classification. If the model is unsure about the category of a text item in the multiple categories classification, it will respond with an empty string for that item. The API will use Python's concurrent.futures module to parallelize the classification of text items. The API will handle timeouts and exceptions by leaving the items unclassified. The API will parse the LLM's response for the multiple categories classification and match it to the list of categories provided in the API parameters. The API will convert the LLM's response and the categories to lowercase before matching them. The API will split the LLM's response on both ':' and ',' to remove the "Category" word from the response. The temperature of the GPT model is set to a minimal value to make the output more deterministic. The API will return all matching categories for a text item in the multiple categories classification. The API will strip any leading or trailing whitespace from the categories in the LLM's response before matching them to the list of categories provided in the API parameters. The API will accept lists as answers from the LLM. If the LLM responds with a string that's formatted like a list, the API will parse it and match it to the list of categories provided in the API parameters.

Icon 1 Icon 1
218

We found some blogs you might like...