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Hi all, My name is Hogi, I’m new to this subreddit, but it seemed like a good place to find people who were interested in chatbots that might be a little more than chatbots. I’m creating a game that’s sort of between being a chatbot and a slice of life simulator. My goal is to create the most realistic chatbots I can that exist in an interactive, 3D world that can be shared with the player. It’s not easy to develop or publish, but if you have access or the ability to use your own API keys, I’ve made it available for free. https://robotpunch.itch.io/project-tango I’m monetizing the game through the adult and NSFW content, so the censored version is totally free to try out with your own keys and to use as a middleman between chatting with GPT, Claude or any other LM Studio, locally hosted model. I don’t do anything as far as logging or storing your data and if you use LM Studio, your chats are never exposed online. The API keys are read from your system environment variables and are never stored, or read as an exposed string in game code. I want to make the best chatbot experience possible and your feedback is critical to helping me shape the best user experience. If the API keys are too much to manage, I’m working on a Patreon integration, where you’ll soon be able to subscribe and get NSFW chatbot access via one of my own servers. But until that’s ready, there’s the Bring Your Own Keys version available today. Thanks all. submitted by /u/RobotPunchGames |
Category: Chat
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Unreal Engine + Chatbots
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Free and safe NSFW AI Chatbot desereves to try
Heyreal.ai has the easiest system for creating bots and extremely efficient review. You can immediately enjoy the robot you have created. The system also analyzes the psychology of the character based on the uploaded images. This will be reflected in the interaction process with the user.
Unlike some of the bots I have come across, Heyreal has no sentence limit and you can use it unlimitedly for a limited time for free. What puzzles me is that it’s obviously free for a limited time, but the website doesn’t close the paid channel, giving users the wrong idea.
submitted by /u/mintown994
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Would you like to ask under what circumstances will you use AI chatbot to chat?
If it wasn’t for boredom, would you take the initiative to find an AI lover to chat with?
submitted by /u/Acrobatic-Stable-987
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How to make an online soccer coach ai?
Hey! I want to build a soccer coach persona or influencer (or whatever you wanna call it).
When someone visits soccercoachme.ai they see a chatbot interface.
The trick is this soccer coach is very rude and swears a lot so I want to use a hugging face uncensored model.
I want the site to handle at least 10 users visiting at the same time.
Thanks for reading and replying!submitted by /u/Sudden-Bread-1730
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How to train LLMs to ask follow up questions
Hi, I am experimenting using LLama for sales/interview call.
One of the major challenge I am facing is training LLMs to ask follow up questions. I havent been able to find a quality dataset to train the model. I tried controlling it through context but it doesnt work accurately.
Other challenge is scalability: the questions would vary from domain to domain. B2B sales call would differ from a B2C call or digital marketing interview call would differ from product manager interview call.
Any research paper/resource/technique that this community has tried would be helpful.
submitted by /u/StrictSir8506
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Companies that implement Chatbots
Hi Guys! I’m a bit curious if you heard about companies wanting to implement internal chatbots for internal processes. I’m asking this because I’m a solution consultant but don’t want to go to salesy or to shady and hide my question behind any weird questions.
I’m asking this because I heard that a lot are looking for but don’t find one or a lot don’t understand how to implement it internally rather than externally (FAQ)
Edit: I’m not promoting anything (I didn’t post any name of the company I’m working at)
submitted by /u/Feisty_Ocelot1394
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Angelbaby.ai review
submitted by /u/jason_jame
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Integrating Twilio WhatsApp API with a Node.js Application
In this article, we will be exploring how to integrate the Twilio WhatsApp API with a Node.js application. Twilio provides an easy-to-use API for integrating messaging services such as WhatsApp into your applications. By the end of this tutorial, you’ll have a functioning Node.js application that can send and receive messages using the Twilio WhatsApp API.
Table of Contents
- Prerequisites
- Setting up a Twilio Account
- Installing the Twilio SDK
- Sending WhatsApp Messages using Twilio
- Receiving WhatsApp Messages using Twilio
- Implementing a Basic Echo Bot
- Conclusion
1. Prerequisites
Before we begin, ensure that you have the following installed on your system:
- Node.js (version 12 or higher)
- npm (Node.js package manager)
- A code editor (e.g., Visual Studio Code)
2. Setting up a Twilio Account
To start using the Twilio API, you need to create an account on their platform. Visit the Twilio website and sign up for a free account. After signing up, follow the instructions to enable the WhatsApp Sandbox. Note down the following details:
- Account SID
- Auth Token
- Sandbox Number
You’ll need these to authenticate your application with Twilio.
3. Installing the Twilio SDK
Create a new directory for your Node.js application and navigate to it in your terminal. Run the following command to initialize a new Node.js project:
npm init -y
Next, install the Twilio SDK by running:
npm install twilio
4. Sending WhatsApp Messages using Twilio
Create a new file called sendWhatsAppMessage.js and open it in your code editor. First, import the Twilio module and initialize a Twilio client using your Account SID and Auth Token:
const twilio = require('twilio');
const accountSid = 'your_account_sid';
const authToken = 'your_auth_token';
const client = new twilio(accountSid, authToken);Replace ‘your_account_sid’ and ‘your_auth_token’ with the respective values from your Twilio account.
Now, create a function to send WhatsApp messages using the Twilio client:
async function sendWhatsAppMessage(to, message) {
try {
const response = await client.messages.create({
body: message,
from: 'whatsapp:+14155238886', // Your Twilio Sandbox Number
to: `whatsapp:${to}`,
});
console.log(`Message sent to ${to}: ${response.sid}`);
} catch (error) {
console.error(`Failed to send message: ${error}`);
}
}
sendWhatsAppMessage('+1234567890', 'Hello from Twilio WhatsApp API!'); // Replace with your phone numberReplace +1234567890 with your own phone number, including the country code, and run the script:
node sendWhatsAppMessage.js
You should receive a WhatsApp message from the Twilio Sandbox number.
5. Receiving WhatsApp Messages using Twilio
To receive WhatsApp messages, you need to set up a webhook for incoming messages. We’ll use the express framework for our web server and ngrok to expose our local server to the internet. Install the required packages:
npm install express ngrok
Create a new file called receiveWhatsAppMessage.js and open it in your code editor. Set up a basic express server
const express = require('express');
const app = express();
const port = 3000;
app.use(express.urlencoded({ extended: false }));
app.post('/incoming', (req, res) => {
const message = req.body;
console.log(Received message from ${message.From}: ${message.Body});
res.status(200).send('OK');
});
app.listen(port, () => {
console.log(Server running on http://localhost:${port});
});In this code, we create an Express server and define a route for incoming messages at `/incoming`. When a message is received, we log the sender’s phone number and message content to the console. Next, expose your local server to the internet using `ngrok`.
Create a new file called `start.js` and add the following code:
const ngrok = require('ngrok');
const { spawn } = require('child_process');
(async () => {
const url = await ngrok.connect(3000);
console.log(`ngrok tunnel opened at ${url}`);
const receiveWhatsAppMessageProcess = spawn('node', ['receiveWhatsAppMessage.js'], { stdio: 'inherit', });
process.on('SIGINT', async () => {
console.log('Shutting down…');
await ngrok.kill();
receiveWhatsAppMessage
Process.kill('SIGINT');
process.exit(0);
});
})();This script starts the ngrok tunnel and runs our receiveWhatsAppMessage.js script as a child process. When the script is terminated, it will close the ngrok tunnel and child process.
Run the start.js script:
node start.js
You should see the ngrok tunnel URL in your console. Copy this URL and add /incoming to the end of it. Update the webhook URL for your Twilio Sandbox number by going to your Twilio Console, selecting your Sandbox number, and pasting the ngrok URL into the “A MESSAGE COMES IN” field. Save the changes.
Now, send a message to your Twilio Sandbox number, and you should see the message details logged in your console.
6. Implementing a Basic Echo Bot
As a practical example, let’s create a simple echo bot that replies to incoming messages. Update the /incoming route in your receiveWhatsAppMessage.js file:
const MessagingResponse = require('twilio').twiml.MessagingResponse;
app.post('/incoming', (req, res) => {
const message = req.body;
console.log(`Received message from ${message.From}: ${message.Body}`);
const twiml = new MessagingResponse();
twiml.message(`You said: ${message.Body}`);
res.writeHead(200, { 'Content-Type': 'text/xml' });
res.end(twiml.toString());
});This code creates a TwiML response using the Twilio SDK’s MessagingResponse class. The response contains a new message with the original message’s content. When Twilio receives the response, it will send the reply to the sender.
Restart your start.js script, and send another message to your Twilio Sandbox number. You should receive a reply with the message content.
Conclusion
In this article, we’ve shown you how to integrate the Twilio WhatsApp API with a Node.js application. You learned how to send and receive messages using the Twilio API, and we demonstrated a simple echo bot example. With these building blocks, you can now create more complex chatbots and integrate WhatsApp messaging into your applications using Node.js and Twilio, In the next article, I’ll explain how to integrate WhatsApp API with ChatGPT.
Integrating Twilio WhatsApp API with a Node.js Application was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.