Purpose : Major Project Team Size : 4 Duration : 10 Months [ Oct. 1, 2021 - June 31, 2022 ] Key Skills : Rasa AI , Python , NLP , Flask , HTML , CSS , JavaScript It is a Web-based Chatbot to automate healthcare management with audio assistance. Users can get immediate medication for their symptoms and book appointments via an audio feature. In addition to text assistance, this chatbot has an audio assistance feature. This feature eliminates the restrictions that visually impaired patients face w
git clone https://github.com/aakif123/Tabib-HealthCare-Chatbot.gitPurpose : Major Project Team Size : 4 Duration : 10 Months [ Oct. 1, 2021 - June 31, 2022 ] Key Skills : Rasa AI , Python , NLP , Flask , HTML , CSS , JavaScript It is a Web-based Chatbot to automate healthcare management with audio assistance. Users can get immediate medication for their symptoms and book appointments via an audio feature. In addition to text assistance, this chatbot has an audio assistance feature. This feature eliminates the restrictions that visually impaired patients face w
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I need to develop a healthcare chatbot using Rasa AI, Python, and NLP. The chatbot should have both text and audio assistance features. It should be able to provide immediate medication recommendations based on symptoms and allow users to book appointments. The target users are [COMPANY] in the [INDUSTRY] sector. Can you provide a detailed plan and code snippets for implementing this chatbot?
# Healthcare Chatbot Development Plan
## Overview
The healthcare chatbot will be developed using Rasa AI, Python, and NLP. It will feature both text and audio assistance to cater to all users, including those with visual impairments. The chatbot will provide immediate medication recommendations and appointment booking functionality.
## Key Features
- **Text Assistance**: Users can input their symptoms via text and receive medication recommendations.
- **Audio Assistance**: Users can interact with the chatbot via voice commands, making it accessible to visually impaired individuals.
- **Appointment Booking**: Users can schedule appointments with healthcare providers directly through the chatbot.
## Implementation Plan
1. **Setup Rasa AI Environment**: Install Rasa AI and configure the development environment.
2. **Develop NLP Models**: Train NLP models to understand user inputs related to symptoms and medication.
3. **Integrate Audio Features**: Implement audio input and output capabilities using Python libraries.
4. **Create User Interface**: Design a user-friendly interface using HTML, CSS, and JavaScript.
5. **Test and Deploy**: Conduct thorough testing and deploy the chatbot on a web platform.
## Code Snippets
```python
# Example code snippet for symptom analysis
from rasa_nlu.training_data import load_data
from rasa_nlu.config import RasaNLUConfig
from rasa_nlu.model import Trainer
def train_nlp_model(data_path, config_path):
training_data = load_data(data_path)
trainer = Trainer(RasaNLUConfig(config_path))
trainer.train(training_data)
model_directory = trainer.persist()
return model_directory
# Example code snippet for audio input
import speech_recognition as sr
def recognize_speech(audio_file):
recognizer = sr.Recognizer()
with sr.AudioFile(audio_file) as source:
audio = recognizer.record(source)
try:
text = recognizer.recognize_google(audio)
return text
except sr.UnknownValueError:
return "Could not understand audio"
except sr.RequestError:
return "API unavailable"
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