- Introduction
- Problem Statement
- Features
- Technologies Used
- Installation
- Usage
- Project Structure
- Architecture
- API Reference
- Testing
- Deployment
- Contributing
- License
- Acknowledgements
The AI-Powered Appointment Scheduling Assistant is an advanced chatbot system designed to streamline the process of scheduling medical appointments. It leverages natural language processing and machine learning to provide a seamless, efficient, and patient-centric scheduling experience for healthcare facilities.
The current process of scheduling and managing medical appointments presents challenges for both patients and healthcare providers. Inefficiencies in the existing system can lead to suboptimal experiences and resource allocation. This project aims to address these issues by providing an AI-powered solution that enhances the appointment booking process.
For a detailed problem statement, please refer to the PROBLEM_STATEMENT.md file.
- 🗣️ Natural language processing for conversational interactions
- 📊 Dynamic information gathering from patients
- 🕒 Real-time availability checking for doctors and specialties
- 🌐 Multilingual support
- 🔒 HIPAA-compliant data handling
- 📅 Appointment confirmation and instructions
- 🚗 Integration with additional services (e.g., parking information, pre-appointment tests)
- Python 3.x
- OpenAI GPT-4 API
- JSON for data structuring
- Rich library for console output formatting
- Colorama for colored terminal output
To start the AI-powered appointment scheduling assistant, run:
python llm-scheduling/chatbot.py
Follow the on-screen prompts to interact with the chatbot and schedule appointments.
File Name | Type | Description |
---|---|---|
llm-scheduling/chatbot.py | Python | Main chatbot script |
task/ARCHITECTURE.md | Markdown | System architecture documentation |
task/PROBLEM_STATEMENT.md | Markdown | Problem statement and solution overview |
task/01-protocol.md | Markdown | Operating procedure protocol for appointment scheduling |
task/prompt.md | Markdown | AI assistant prompt and guidelines |
task/sample.json | JSON | Sample JSON structure for appointment data |
The system architecture is documented in detail in the ARCHITECTURE.md file. Here's a high-level overview of the system:
graph TD
A[User] -->|Interacts with| B[Chatbot Interface]
B -->|Sends requests| C[OpenAI API]
C -->|Returns responses| B
B -->|Retrieves/Updates| D[Appointment Database]
B -->|Checks| E[Doctor Availability]
B -->|Sends| F[Notifications]
The project uses the OpenAI GPT-4 API for natural language processing. For detailed information on the API usage, please refer to the OpenAI API documentation.
This project is licensed under the MIT License. See the LICENSE file for details.
- OpenAI for providing the GPT-4 API
- Contributors and maintainers of the open-source libraries used in this project
- Healthcare professionals who provided valuable insights into the appointment scheduling process