| import streamlit as st | |
| from transformers import pipeline | |
| import nltk | |
| nltk.download('punkt') | |
| nltk.download('stopwords') | |
| chatbot = pipeline("text-generation", model="distilgpt2") | |
| def healthcare_chatbot(user_input): | |
| if "symptom" in user_input: | |
| return "It seems like you're experiencing symptoms. Please consult a doctor for accurate advice." | |
| elif "appointment" in user_input: | |
| return "Would you like me to schedule an appointment with a doctor?" | |
| elif "medication" in user_input: | |
| return "It's important to take your prescribed medications regularly. If you have concerns, consult your doctor." | |
| else: | |
| response = chatbot(user_input, max_length=300, num_return_sequences=1) | |
| return response[0]['generated_text'] | |
| def main(): | |
| st.title("Healthcare Assistant Chatbot") | |
| user_input = st.text_input("How can I assist you today?", "") | |
| if st.button("Submit"): | |
| if user_input: | |
| st.write("User: ", user_input) | |
| response = healthcare_chatbot(user_input) | |
| st.write("Healthcare Assistant: ", response) | |
| else: | |
| st.write("Please enter a query.") | |
| if __name__ == "__main__": | |
| main() | |