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professional-ai-chatbot

v1.1.11

Published

A professional AI chatbot web component

Downloads

4,810

Readme

Professional AI Chatbot

A customizable, professional-looking AI chatbot web component that can be integrated into any web application, regardless of the framework or library you're using.

Table of Contents

Installation

You can install the chatbot component using npm:

npm install professional-ai-chatbot

Alternatively, you can use it directly via a CDN:

<script type="module" src="https://unpkg.com/[email protected]/dist/chatbot.js"></script>

Usage

Basic HTML

To use the chatbot in a basic HTML file, include the script and use the custom element:

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>AI Chatbot Demo</title>
    <script type="module" src="https://unpkg.com/[email protected]/dist/chatbot.js"></script>
</head>
<body>
    <chat-bot
        endpoint="https://your-api-endpoint.com"
        heading="AI Assistant"
        theme="dark"
        initial-model="gpt-4o"
        initial-temperature="0.7"
        initial-max-tokens="2048"
        initial-top-p="0.9"
    ></chat-bot>
</body>
</html>

React

For React applications, create a wrapper component:

import React, { useEffect, useRef } from 'react';
import 'professional-ai-chatbot';

const ChatBotWrapper = (props) => {
  const chatbotRef = useRef(null);

  useEffect(() => {
    if (chatbotRef.current) {
      // You can add event listeners or interact with the web component here if needed
    }
  }, []);

  return <chat-bot ref={chatbotRef} {...props} />;
};

export default ChatBotWrapper;

Then use it in your React components:

import React from 'react';
import ChatBotWrapper from './ChatBotWrapper';

function App() {
  return (
    <div className="App">
      <h1>My React App with AI Chatbot</h1>
      <ChatBotWrapper
        endpoint="https://your-api-endpoint.com"
        heading="AI Assistant"
        theme="dark"
        initialModel="gpt-4o"
        initialTemperature={0.7}
        initialMaxTokens={2048}
        initialTopP={0.9}
      />
    </div>
  );
}

export default App;

Vue.js

For Vue.js applications, create a wrapper component:

<!-- ChatBotWrapper.vue -->
<template>
  <chat-bot
    :endpoint="endpoint"
    :heading="heading"
    :theme="theme"
    :initial-model="initialModel"
    :initial-temperature="initialTemperature"
    :initial-max-tokens="initialMaxTokens"
    :initial-top-p="initialTopP"
  ></chat-bot>
</template>

<script>
import 'professional-ai-chatbot';

export default {
  name: 'ChatBotWrapper',
  props: {
    endpoint: String,
    heading: String,
    theme: String,
    initialModel: String,
    initialTemperature: Number,
    initialMaxTokens: Number,
    initialTopP: Number
  },
  mounted() {
    // You can add event listeners or interact with the web component here if needed
  }
}
</script>

Use it in your Vue components:

<template>
  <div id="app">
    <h1>My Vue App with AI Chatbot</h1>
    <ChatBotWrapper
      endpoint="https://your-api-endpoint.com"
      heading="AI Assistant"
      theme="dark"
      initialModel="gpt-4o"
      :initialTemperature="0.7"
      :initialMaxTokens="2048"
      :initialTopP="0.9"
    />
  </div>
</template>

<script>
import ChatBotWrapper from './ChatBotWrapper.vue'

export default {
  name: 'App',
  components: {
    ChatBotWrapper
  }
}
</script>

Angular

For Angular applications, create a wrapper component:

// chat-bot-wrapper.component.ts
import { Component, Input, AfterViewInit, ElementRef, ViewChild } from '@angular/core';
import 'professional-ai-chatbot';

@Component({
  selector: 'app-chat-bot-wrapper',
  template: `
    <chat-bot
      #chatBot
      [attr.endpoint]="endpoint"
      [attr.heading]="heading"
      [attr.theme]="theme"
      [attr.initial-model]="initialModel"
      [attr.initial-temperature]="initialTemperature"
      [attr.initial-max-tokens]="initialMaxTokens"
      [attr.initial-top-p]="initialTopP"
    ></chat-bot>
  `
})
export class ChatBotWrapperComponent implements AfterViewInit {
  @ViewChild('chatBot') chatBotElement: ElementRef;

  @Input() endpoint: string;
  @Input() heading: string;
  @Input() theme: string;
  @Input() initialModel: string;
  @Input() initialTemperature: number;
  @Input() initialMaxTokens: number;
  @Input() initialTopP: number;

  ngAfterViewInit() {
    // You can add event listeners or interact with the web component here if needed
  }
}

Use it in your Angular components:

<!-- app.component.html -->
<h1>My Angular App with AI Chatbot</h1>
<app-chat-bot-wrapper
  endpoint="https://your-api-endpoint.com"
  heading="AI Assistant"
  theme="dark"
  initialModel="gpt-4o"
  [initialTemperature]="0.7"
  [initialMaxTokens]="2048"
  [initialTopP]="0.9"
></app-chat-bot-wrapper>

Remember to declare the ChatBotWrapperComponent in your app.module.ts and add it to the declarations array.

Svelte

For Svelte applications, create a wrapper component:

<!-- ChatBotWrapper.svelte -->
<svelte:options tag="chat-bot-wrapper" />

<script>
  import 'professional-ai-chatbot';
  import { onMount } from 'svelte';

  export let endpoint;
  export let heading;
  export let theme;
  export let initialModel;
  export let initialTemperature;
  export let initialMaxTokens;
  export let initialTopP;

  let chatBotElement;

  onMount(() => {
    // You can add event listeners or interact with the web component here if needed
  });
</script>

<chat-bot
  bind:this={chatBotElement}
  {endpoint}
  {heading}
  {theme}
  initial-model={initialModel}
  initial-temperature={initialTemperature}
  initial-max-tokens={initialMaxTokens}
  initial-top-p={initialTopP}
></chat-bot>

Use it in your Svelte app:

<!-- App.svelte -->
<script>
  import ChatBotWrapper from './ChatBotWrapper.svelte';
</script>

<h1>My Svelte App with AI Chatbot</h1>
<ChatBotWrapper
  endpoint="https://your-api-endpoint.com"
  heading="AI Assistant"
  theme="dark"
  initialModel="gpt-4o"
  initialTemperature={0.7}
  initialMaxTokens={2048}
  initialTopP={0.9}
/>

API Reference

The chat-bot component accepts the following attributes:

  • endpoint (required): The API endpoint for the chatbot backend.
  • heading (optional): The title displayed in the chat window. Default: "AI Assistant"
  • theme (optional): The color theme of the chatbot. Can be "light" or "dark". Default: "dark"
  • initial-model (optional): The initial AI model to use. Default: "gpt-4o"
  • initial-temperature (optional): The initial temperature setting for the AI. Default: 1
  • initial-max-tokens (optional): The initial maximum number of tokens for AI responses. Default: 4096
  • initial-top-p (optional): The initial top-p setting for the AI. Default: 1

Styling

The chatbot component comes with built-in styles that adapt to light and dark themes. If you need to customize the styles further, you can target the chat-bot element and its internal elements in your CSS.

For example:

chat-bot {
  --chat-primary-color: #3182ce;
  --chat-bg-color: #1a202c;
  --chat-text-color: #ffffff;
}

Browser Support

This web component is compatible with all modern browsers that support Custom Elements v1. This includes:

  • Chrome 54+
  • Firefox 63+
  • Safari 10.1+
  • Edge 79+

For older browsers, you may need to use polyfills.

Troubleshooting

  1. The chatbot is not rendering: Ensure that you've properly imported the component and that your browser supports Custom Elements v1.

  2. Styling conflicts: If you're experiencing styling issues, try increasing the specificity of your custom styles or use Shadow DOM piercing combinators carefully.

  3. Console errors: Check the browser console for any error messages. Common issues include incorrect API endpoints or CORS restrictions.

Contributing

We welcome contributions to improve the chatbot component. Please follow these steps:

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add some AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE.md file for details.