Skip to main content

genZ_Chatbot is a beginner-friendly Python package that guides users through building AI chatbots from the ground up. It supports multiple LLMs and offers customizable behavior and design, making chatbot development simpler while teaching essential Generative AI concepts.

Project description

genZ_Chatbot: Your Gateway to AI Chatbot Creation! 🤖✨

Welcome to genZ_Chatbot, the ultimate package designed to help beginners build AI chatbots from scratch. Whether you're just stepping into the world of Generative AI or looking to understand chatbot integration, GenZBot has got you covered! It provides a step-by-step guide to walk you through the entire process. 📦


Features 🌟

  • Easy Setup: Create an AI chatbot project structure with a single command.
  • Multiple LLMs: Choose from 5 powerful language models:
    • openai 🔑 (requires a paid API key from OpenAI)
    • gemini 🌌 (free API key from Google AI Studio)
    • gemma 🧠 (all these other three have free API key from Groq)
    • llama 🦙
    • mixtral 🌀
  • Customizable Templates: Two designs available:
    • Plain
    • Galaxy 🌠
  • Personalization: Set your bot's behavior and name easily.
  • Automated Environment Setup: Virtual environment creation, dependency installation, and app execution are just one command away.

Installation 🛠️

  1. Install genZ_Chatbot using pip:

    pip install genZ_Chatbot
    
  2. Import the ChatBot class:

    from genZ_Chatbot.chatbot import ChatBot
    

Getting Started 🚀

Here’s how to create your first chatbot project with genZ_Chatbot:

  1. Initialize Your ChatBot:

    bot = ChatBot(llm='gemini', api_key='your-api-key')
    
  2. Create Project Structure:

    bot.CreateProject()
    

    This command will generate the following structure:

    Chatbot_Project/
        AI_Service/
            AIResponse.py
        Backend/
            app.py
        Frontend/
            static/
                static.js
                style.css
            templates/
                index.html
        .env
        requirements
    
  3. Run the ChatBot:

    bot.run()
    

    This command will:

    • Create a virtual environment.
    • Install all dependencies from requirements.
    • Launch the Flask app.

Example Code 📝

from genZ_Chatbot.chatbot import ChatBot

# Step 1: Initialize ChatBot
bot = ChatBot(llm='gemini', api_key='your-api-key')

# Step 2: Create Project Structure
bot.CreateProject()

# Step 3: Run the Bot
bot.run()

API Keys 🔑

  • OpenAI: Obtain a paid API key from OpenAI.
  • Gemini: Get a free API key from Google AI Studio.
  • Gemma, Llama, Mixtral: Request API keys from Groq AI.

Why Choose GenZBot? 🤔

  • Ideal for beginners looking to explore Generative AI.
  • Provides a clear project structure for understanding AI chatbot integration.
  • Saves time with automated setup and environment configuration.

Happy Chatbot Building! 🎉

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

genz_chatbot-0.0.3.tar.gz (8.6 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

genz_chatbot-0.0.3-py3-none-any.whl (8.6 MB view details)

Uploaded Python 3

File details

Details for the file genz_chatbot-0.0.3.tar.gz.

File metadata

  • Download URL: genz_chatbot-0.0.3.tar.gz
  • Upload date:
  • Size: 8.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.4

File hashes

Hashes for genz_chatbot-0.0.3.tar.gz
Algorithm Hash digest
SHA256 0f0865beb7943df6bbd9d3d333a1a0e1cc60728c23e1e1a103e36b88b3eb9dcd
MD5 45249e3cb6031180c10c30133d2854a8
BLAKE2b-256 17c449872c0e479f4c94e72c34ea4b38c3f165f5fcc739c4bdba4b8c4f0ff908

See more details on using hashes here.

File details

Details for the file genz_chatbot-0.0.3-py3-none-any.whl.

File metadata

  • Download URL: genz_chatbot-0.0.3-py3-none-any.whl
  • Upload date:
  • Size: 8.6 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.4

File hashes

Hashes for genz_chatbot-0.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 ecfb7c16a79c1182457fdc8ee61d5516fc052d2b6310f74c72662f100cf0ae6f
MD5 aa6b3c701492f5997f43c33467a12913
BLAKE2b-256 3edb83da3601a777911eeb594f0f005a5ec2234252d6a8310f3aa7b0ecfe589c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page