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2024-10-12 14:46:15 -07:00
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# Simple Chatbot
# Patient-intake chatbot
<img src="image.png" width="420px">
This app connects you to a chatbot powered by GPT-4, complete with animations generated by Stable Video Diffusion.
This project implements an AI-powered chatbot designed to streamline the medical intake process for Tri-County Health Services. The chatbot, named Jessica, interacts with patients to collect essential information before their doctor's visit, enhancing efficiency and improving the patient experience.
See a video of it in action: https://x.com/kwindla/status/1778628911817183509
## Features
And a quick video walkthrough of the code: https://www.loom.com/share/13df1967161f4d24ade054e7f8753416
Identity Verification: Confirms patient identity by verifying their date of birth.
Prescription Information: Collects details about current medications and dosages.
Allergy Documentation: Records patient allergies.
Medical Conditions: Gathers information about existing medical conditions.
Reason for Visit: Asks patients about the purpose of their current doctor's visit.
## Technical Stack
Language: Python
AI Model: OpenAI's GPT-4
Text-to-Speech: Cartesia TTS Service
Audio Processing: Silero VAD (Voice Activity Detection)
Real-time Communication: Daily.co API
## Key Components
IntakeProcessor: Manages the conversation flow and information gathering process.
DailyTransport: Handles real-time audio communication.
CartesiaTTSService: Converts text responses to speech.
OpenAILLMService: Processes natural language and generates appropriate responses.
Pipeline: Orchestrates the flow of information between different components.
How It Works
The chatbot introduces itself and verifies the patient's identity.
It systematically collects information about prescriptions, allergies, medical conditions, and the reason for the visit.
The conversation is guided by a series of function calls that transition between different stages of the intake process.
All collected information is logged for later use by medical professionals.
ℹ️ The first time, things might take extra time to get started since VAD (Voice Activity Detection) model needs to be downloaded.