Athlete's Temple Business Chatbot

A sophisticated business chatbot built with Gradio and OpenAI/Gemini that serves as an intelligent concierge for Athlete's Temple fitness and martial arts club.

Hugging Face Link

https://huggingface.co/spaces/bob-t/gym-manager-chatbot-agent/tree/main

Features

• Intelligent Q&A: Answers questions about the business using a comprehensive knowledge base
• Lead Collection: Automatically captures customer interest and contact information
• Feedback Logging: Records unanswered questions for follow-up by staff
• Tool Integration: Uses OpenAI function calling for automated data collection
• Mobile-Friendly UI: Built with Gradio for responsive web interface
• Dual Provider Support: Works with both OpenAI and Gemini APIs

Project Structure

├── business_agent.ipynb          # Main Jupyter notebook with chatbot implementation
├── feedback.csv                  # Logged unanswered questions and feedback
├── leads.csv                     # Collected customer leads and contact information
├── me/
│   ├── business_summary.txt      # Core business knowledge base
│   └── about business.pdf        # Additional business documentation
├── 1. C3 - Assignment.pdf        # Assignment instructions
├── requirements.txt              # Python dependencies
└── README.md                     # This file

Setup Instructions

Prerequisites

• Python 3.8+
• OpenAI API key or Gemini API key

Installation

1. Clone this repository:

git clone <repository-url>
cd athlete-temple-chatbot

2. Install dependencies:

pip install -r requirements.txt

3. Set up environment variables: Create a .env file in the project root:

OPENAI_API_KEY=your_openai_api_key_here
PROVIDER=openai
OPENAI_MODEL=gpt-4o-mini
OPENAI_TEMPERATURE=0.6
OPENAI_TOP_P=0.9
OPENAI_MAX_TOKENS=400

Running the Application

1. Open the Jupyter notebook:

jupyter notebook business_agent.ipynb

2. Run all cells to start the application

3. The Gradio interface will launch automatically with a local URL and public sharing link

How It Works

Knowledge Base

The chatbot uses me/business_summary.txt as its authoritative source of information about Athlete's Temple, including:

• Mission and services
• Team member profiles
• Unique value propositions

Tool Functions

The chatbot includes two main tools:

1. record_customer_interest: Captures customer contact information and notes when they express interest
2. record_feedback: Logs questions that couldn't be answered from the knowledge base

Data Collection

• Leads: Stored in leads.csv with timestamp, name, email, notes, and source
• Feedback: Stored in feedback.csv with timestamp, user message, status, and tags

Usage Examples

Customer Questions

• "What martial arts classes do you offer?"
• "Tell me about your personal training programs"
• "Who are your coaches?"

Lead Collection

When customers express interest or ask questions not covered in the knowledge base, the chatbot automatically:

1. Logs the interaction
2. Asks for contact information
3. Saves the lead for follow-up

Technical Details

Architecture

• Frontend: Gradio web interface
• Backend: OpenAI API with function calling
• Data Storage: CSV files for leads and feedback
• Knowledge Management: Text-based business summary

Key Components

• agentic_chat_once(): Core chat function with tool calling
• record_customer_interest(): Lead capture functionality
• record_feedback(): Feedback logging system
• Gradio UI with multiple tabs for chat, leads, and logs

Configuration

The application supports various configuration options through environment variables:

• PROVIDER: Choose between "openai" or "gemini"
• OPENAI_MODEL: Specify the OpenAI model to use
• OPENAI_TEMPERATURE: Control response creativity (0.0-1.0)
• OPENAI_TOP_P: Control response diversity (0.0-1.0)
• OPENAI_MAX_TOKENS: Limit response length

Data Privacy

• All customer data is stored locally in CSV files
• No data is sent to external services except for AI processing
• Sensitive information should be handled according to privacy regulations

Future Enhancements

• Integration with CRM systems
• Email automation for lead follow-up
• Analytics dashboard for lead conversion
• Multi-language support
• Voice interface integration

License

This project is part of an academic assignment for EECE 798S course.

Contact

For questions about this implementation, please refer to the assignment documentation or course instructor.