In the age of digital transformation, businesses are increasingly turning to AI-driven solutions to enhance productivity and streamline operations. One such innovation is the AI chatbot, a tool that can revolutionize customer interactions and provide valuable business insights. In this article, we delve into the development of an AI Business Assistant Chatbot using Streamlit and OpenAI’s GPT-3.5-turbo model. This project showcases how to build a user-friendly application that leverages the power of AI to assist with business queries, manage conversations, and tailor responses based on user input.
The AI Business Assistant Chatbot is a web-based application designed to interact with users in a conversational manner. It employs the GPT-3.5-turbo model from OpenAI, known for its advanced natural language processing capabilities. The application, built using Streamlit, allows users to engage in dynamic conversations with an AI assistant that can adopt various personas based on the user’s preferences.
- Dynamic Personas: Users can switch between predefined personas or set a custom system message to personalize the assistant’s responses.
- Interactive Chat: A user-friendly interface for engaging with the AI assistant.
- Conversation History Management: Users can manage and reset conversation history to maintain context or start afresh.
- Token Management: Efficient use of API tokens is enforced to manage costs and optimize performance.
To get started with this project, you need to set up your environment and understand the core components of the application. Let’s walk through the process of setting up the project and exploring its features.
- Clone the Repository
Begin by cloning the repository from GitHub:
git clone https://github.com/Huzaifaaazhar/AI-Business-Assistant-Bot.git
cd AI-Business-Assistant-BotCreate and Activate a Virtual Environment
2. Create a virtual environment to manage dependencies:
python -m venv .venv
For Windows:
.\.venv\Scripts\activate
For macOS/Linux:
source .venv/bin/activate
3. Install Dependencies
Install the necessary Python packages:
pip install -r requirements.txt
4. Configure API Key
Create a `.env` file in the root directory with your OpenAI API key:
OPENAI_API_KEY=your_openai_api_key
Make sure the `.env` file is listed in your `.gitignore` to keep it secure.
Let’s delve into the core components of the AI Business Assistant Chatbot application.
AI Virtual Assistant.py
This is the main script that powers the Streamlit application. It contains the user interface and logic for interacting with the AI assistant.
The script starts by importing necessary libraries:
import streamlit as st
from openai import OpenAI
from dotenv import load_dotenv
import os
- streamlit is used to create the web interface.
- OpenAI provides access to the GPT-3.5-turbo model.
- dotenv loads environment variables from the `.env` file.
- os is used for file operations.
The API key is loaded from the `.env` file:
load_dotenv()
OPENAI_API_KEY = os.getenv(‘OPENAI_API_KEY’)
The interface is set up with Streamlit’s configuration options:
st.set_page_config(page_title=”AI Business Assistant”, page_icon=”????”)
This configures the page title and icon.
The sidebar allows users to select personas and manage the conversation:
st.sidebar.title(“AI Business Assistant”)
persona_option = st.sidebar.selectbox(
“Select Persona”,
[“Empathetic”, “Thoughtful”, “Strategic”, “Owner”, “Custom”]
)
Users can choose from predefined personas or enter a custom message.
- Dynamic Personas: The application allows users to interact with the chatbot in different personas, such as Empathetic, Thoughtful, Strategic, and Owner. Users can also set a custom system message to tailor the assistant’s responses to their needs.
- Interactive Chat: The chat interface provides an intuitive way for users to engage with the AI assistant. Users can type their messages and receive responses in real time, making the interaction seamless and engaging.
- Conversation History Management: The application manages conversation history to maintain context and continuity. Users can reset the conversation history if they wish to start a new session, ensuring a clean slate for each interaction.
- Token Management: The chatbot efficiently manages API tokens to optimize performance and control costs. The token budget is enforced to ensure that responses are generated within the specified limits.
## Running the Application
To run the AI Business Assistant Chatbot, follow these steps:
streamlit run AI\ Virtual\ Assistant.py
Open your web browser and navigate to `http://localhost:8501` to interact with the chatbot.
- Select Persona: Choose a persona from the sidebar or enter a custom system message.
- Engage in Chat: Type a message in the input box and press Enter. The chatbot will respond based on the selected persona and conversation context.
- Manage History: Use the “Reset Conversation History” button to start a new conversation if needed.
The AI Business Assistant Chatbot is a powerful tool that leverages OpenAI’s GPT-3.5-turbo model to provide dynamic and personalized interactions. Built using Streamlit, this application offers a user-friendly interface for managing conversations and adapting the assistant’s behavior to various personas. With features such as conversation history management and token optimization, it demonstrates how AI can be harnessed to enhance business interactions and provide valuable insights.
Whether you’re looking to deploy a chatbot for customer support, business queries, or any other purpose, the principles and components outlined in this article can help you build a robust and effective solution.