Introduction to ChatBotAI Project
The ChatBotAI project is an innovative Python-based artificial intelligence tool designed to simplify the development of chatbots. This tool provides a robust framework for creating bots with advanced features through minimal coding, making it accessible to developers at various skill levels.
Key Features
ChatBotAI differentiates itself with a wide array of functionalities. It offers intuitive bot AI and chat handlers, along with easy integration of REST APIs and Python function calls. Some of its distinctive features include:
- Learn and Memory: The chatbot can learn from interactions and remember information, enhancing user experience over time.
- Conditional Switches and Topic-based Conversations: This allows the bot to handle different topics and conditions dynamically, making conversations more natural and relevant.
- Interactivity with Python Functions: Users can register Python functions to be called during conversations, adding custom functionality to the bot.
- REST API Integration: ChatBotAI can integrate with web services, enabling the bot to access additional information and functionalities from the internet.
Installation
ChatBotAI can be installed via two methods:
-
PyPI: Install using the Python package manager with the command:
pip install chatbotAI -
GitHub: Clone the repository and install using:
git clone https://github.com/ahmadfaizalbh/Chatbot.git cd Chatbot python setup.py install
Getting Started
To see ChatBotAI in action, users can try out the demo feature:
>>> from chatbot import demo
>>> demo()
This simple interaction demonstrates the bot's conversational ability.
Sample Code
ChatBotAI offers integrations like a sample code for incorporating Wikipedia search API, which allows the bot to fetch summaries from Wikipedia, enhancing its response quality:
from chatbot import Chat, register_call
import wikipedia
@register_call("whoIs")
def who_is(session, query):
try:
return wikipedia.summary(query)
except Exception:
return "I don't know about "+query
first_question="Hi, how are you?"
Chat("examples/Example.template").converse(first_question)
Advanced Features
- Memory Management: Users can store and retrieve information dynamically within conversations.
- Regular Expressions: ChatBotAI utilizes regex to match conversation patterns efficiently.
- API Integrations: Customize API calls and process JSON responses seamlessly in conversational templates.
- Custom Responses and Conditions: The bot can perform actions based on dynamic conditions and change topics under specific scenarios.
- Learning Capabilities: The bot can be programmed to learn new conversation paths based on user input.
Sample Applications
ChatBotAI's versatility is demonstrated in various applications:
- Facebook Messenger Bot: Built using Django and NLTK-Chatbot, providing a practical example of social media integration.
- Microsoft Chatbot: Utilizes the Microsoft Bot Connector Rest API for corporate communication tools.
Overall, ChatBotAI presents a dynamic and powerful platform for developers looking to create intelligent, responsive chatbots with customizable features and functionalities. Its ability to integrate with Python functions and REST APIs makes it suitable for various applications, from simple personal assistants to complex enterprise bots.