AI Voice Assistant & Chatbot

AI Voice Assistant & Chatbot for Clinics using Local LLM & OpenAI Realtime API. Customers can ask questions about the clinic and get answers. Appointment booking, prescription management, and custom actions are supported in this project.
Technologies Used:
AILocal LLMOpenAI APIRagLangChainSpeech-to-TextText-to-SpeechNode.js
AI Voice Assistant & Chatbot
Overview
This project is a comprehensive AI Voice Assistant and Chatbot system developed for clinics. Using Local LLM and OpenAI Realtime API, it is designed to allow customers to ask questions about the clinic, make appointments, and manage prescriptions.
Key Features
Voice Assistant Capabilities
- Natural Language Processing: Natural language understanding and processing
- Real-time Voice Interaction: Real-time voice interaction
- Multi-language Support: Multi-language support
- Context Awareness: Context preservation in conversations
Chatbot Features
- 24/7 Availability: 24/7 customer service
- Instant Responses: Instant response capability
- FAQ Management: Automatic answering of frequently asked questions
- Escalation to Human: Escalation to human operators when needed
Healthcare-Specific Functions
- Appointment Booking: Appointment scheduling and management
- Prescription Management: Prescription inquiry and tracking
- Medical Information: Providing basic health information
- Emergency Protocols: Emergency protocols
Technical Architecture
AI/ML Components
- Local LLM: Privacy-focused local language model
- OpenAI Realtime API: Real-time AI interaction
- RAG (Retrieval-Augmented Generation): Knowledge base integration
- LangChain: AI application development framework
Voice Processing
- Speech-to-Text: Converting voice commands to text
- Text-to-Speech: Converting text to natural speech
- Voice Recognition: User voice recognition
- Noise Cancellation: Noise filtering
Integration Layer
- Clinic Management System: Clinic management system integration
- Calendar API: Appointment calendar integration
- Patient Database: Patient database connection
- Prescription System: Prescription system integration
Implementation Details
Local LLM Setup
- Model Selection: Performance and privacy balance
- Hardware Requirements: GPU and RAM optimization
- Model Fine-tuning: Customization for clinical terminology
- Performance Monitoring: Model performance tracking
OpenAI Integration
- Realtime API: Real-time interaction
- Custom Actions: Defining custom actions
- Context Management: Conversation history management
- Error Handling: Error handling and fallback mechanisms
Security & Privacy
- Data Encryption: Data encryption
- HIPAA Compliance: Health data protection
- Access Control: Access control
- Audit Logging: Audit logging
Business Benefits
Operational Efficiency
- %60 Reduction in customer service calls
- %40 Faster appointment booking process
- 24/7 Availability without additional staff
Customer Experience
- Instant Response: Instant customer support
- Multilingual Support: Multilingual support
- Personalized Service: Personalized service
- Reduced Wait Times: Reduced wait times
Cost Savings
- Staff Reduction: Reduced staff costs
- Automated Processes: Automated processes
- Reduced Errors: Reduced error rates
Use Cases
Appointment Management
- Appointment scheduling and rescheduling
- Doctor availability inquiry
- Appointment reminders
- Cancellation and postponement operations
Prescription Services
- Prescription inquiry
- Medication information
- Dosage instructions
- Side effect information
General Information
- Information about the clinic
- Doctor profiles
- Service catalog
- Contact information
Future Enhancements
- Telemedicine Integration: Telemedicine integration
- Wearable Device Support: Wearable device support
- Advanced Analytics: Advanced analytics features
- Mobile App Integration: Mobile app integration
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Son güncelleme: 15 Kasım 2024