nice

a.py

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+import gradio as gr
+
+def greet(name):
+    return "Hello " + name + "!!"
+
+iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+iface.launch()

app.py

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+# Import and class names setup
+import gradio as gr
+import os
+import torch
+import random
+#import nltk_utils
+import pandas as pd
+from sklearn.model_selection import train_test_split
+import time
+
+#from model import RNN_model
+from timeit import default_timer as timer
+from typing import Tuple, Dict
+
+# Import data
+df= pd.read_csv('Symptom2Disease.csv')
+df.drop('Unnamed: 0', axis= 1, inplace= True)
+
+# Preprocess data
+df.drop_duplicates(inplace= True)
+train_data, test_data= train_test_split(df, test_size=0.15, random_state=42 )
+
+# Setup class names
+class_names= {0: 'Acne',
+              1: 'Arthritis',
+              2: 'Bronchial Asthma',
+              3: 'Cervical spondylosis',
+              4: 'Chicken pox',
+              5: 'Common Cold',
+              6: 'Dengue',
+              7: 'Dimorphic Hemorrhoids',
+              8: 'Fungal infection',
+              9: 'Hypertension',
+              10: 'Impetigo',
+              11: 'Jaundice',
+              12: 'Malaria',
+              13: 'Migraine',
+              14: 'Pneumonia',
+              15: 'Psoriasis',
+              16: 'Typhoid',
+              17: 'Varicose Veins',
+              18: 'allergy',
+              19: 'diabetes',
+              20: 'drug reaction',
+              21: 'gastroesophageal reflux disease',
+              22: 'peptic ulcer disease',
+              23: 'urinary tract infection'
+              }
+
+#vectorizer= nltk_utils.vectorizer()
+#vectorizer.fit(train_data.text)
+
+
+
+# Model and transforms preparation
+#model= RNN_model()
+# Load state dict
+#model.load_state_dict(torch.load(
+#    f= 'pretrained_symtom_to_disease_model.pth',
+#    map_location= torch.device('cpu'))
+# Disease Advice
+disease_advice = {
+    'Acne': "Maintain a proper skincare routine, avoid excessive touching of the affected areas, and consider using over-the-counter topical treatments. If severe, consult a dermatologist.",
+    'Arthritis': "Stay active with gentle exercises, manage weight, and consider pain-relief strategies like hot/cold therapy. Consult a rheumatologist for tailored guidance.",
+    'Bronchial Asthma': "Follow prescribed inhaler and medication regimen, avoid triggers like smoke and allergens, and have an asthma action plan. Regular check-ups with a pulmonologist are important.",
+    'Cervical spondylosis': "Maintain good posture, do neck exercises, and use ergonomic support. Physical therapy and pain management techniques might be helpful.",
+    'Chicken pox': "Rest, maintain hygiene, and avoid scratching. Consult a doctor for appropriate antiviral treatment.",
+    'Common Cold': "Get plenty of rest, stay hydrated, and consider over-the-counter remedies for symptom relief. Seek medical attention if symptoms worsen or last long.",
+    'Dengue': "Stay hydrated, rest, and manage fever with acetaminophen. Seek medical care promptly, as dengue can escalate quickly.",
+    'Dimorphic Hemorrhoids': "Follow a high-fiber diet, maintain good hygiene, and consider stool softeners. Consult a doctor if symptoms persist.",
+    'Fungal infection': "Keep the affected area clean and dry, use antifungal creams, and avoid sharing personal items. Consult a dermatologist if it persists.",
+    'Hypertension': "Follow a balanced diet, exercise regularly, reduce salt intake, and take prescribed medications. Regular check-ups with a healthcare provider are important.",
+    'Impetigo': "Keep the affected area clean, use prescribed antibiotics, and avoid close contact. Consult a doctor for proper treatment.",
+    'Jaundice': "Get plenty of rest, maintain hydration, and follow a doctor's advice for diet and medications. Regular monitoring is important.",
+    'Malaria': "Take prescribed antimalarial medications, rest, and manage fever. Seek medical attention for severe cases.",
+    'Migraine': "Identify triggers, manage stress, and consider pain-relief medications. Consult a neurologist for personalized management.",
+    'Pneumonia': "Follow prescribed antibiotics, rest, stay hydrated, and monitor symptoms. Seek immediate medical attention for severe cases.",
+    'Psoriasis': "Moisturize, use prescribed creams, and avoid triggers. Consult a dermatologist for effective management.",
+    'Typhoid': "Take prescribed antibiotics, rest, and stay hydrated. Dietary precautions are important. Consult a doctor for proper treatment.",
+    'Varicose Veins': "Elevate legs, exercise regularly, and wear compression stockings. Consult a vascular specialist for evaluation and treatment options.",
+    'allergy': "Identify triggers, manage exposure, and consider antihistamines. Consult an allergist for comprehensive management.",
+    'diabetes': "Follow a balanced diet, exercise, monitor blood sugar levels, and take prescribed medications. Regular visits to an endocrinologist are essential.",
+    'drug reaction': "Discontinue the suspected medication, seek medical attention if symptoms are severe, and inform healthcare providers about the reaction.",
+    'gastroesophageal reflux disease': "Follow dietary changes, avoid large meals, and consider medications. Consult a doctor for personalized management.",
+    'peptic ulcer disease': "Avoid spicy and acidic foods, take prescribed medications, and manage stress. Consult a gastroenterologist for guidance.",
+    'urinary tract infection': "Stay hydrated, take prescribed antibiotics, and maintain good hygiene. Consult a doctor for appropriate treatment."
+}
+
+howto= """Welcome to the <b>Medical Chatbot</b>, powered by Gradio.
+Currently, the chatbot can WELCOME YOU, PREDICT DISEASE based on your symptoms and SUGGEST POSSIBLE SOLUTIONS AND RECOMENDATIONS, and BID YOU FAREWELL.
+<br><br>
+Here's a quick guide to get you started:<br><br>
+<b>How to Start:</b> Simply type your messages in the textbox to chat with the Chatbot and press enter!<br><br>
+The bot will respond based on the best possible answers to your messages. For now, let's keep it SIMPLE as I'm working hard to enhance its capabilities in the future.
+
+"""
+
+
+# Create the gradio demo
+with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;} #chatbot {height: 520px; overflow: auto;}""") as demo:
+  gr.HTML('<h1 align="center">Medical Chatbot: Your Virtual Health Guide 🌟🏥🤖"</h1>')
+  gr.HTML('<h3 align="center">To know more about this project click, <a href="https://github.com/Monsurat-Onabajo/Medical_chatbot" target="_blank">Here</a>')
+  with gr.Accordion("Follow these Steps to use the Gradio WebUI", open=True):
+      gr.HTML(howto)
+  chatbot = gr.Chatbot()
+  msg = gr.Textbox()
+  clear = gr.ClearButton([msg, chatbot])
+
+  def respond(message, chat_history):
+    # Random greetings in list format
+    greetings = [
+        "hello!",'hello', 'hii !', 'hi', "hi there!",  "hi there!", "heyy", 'good morning', 'good afternoon', 'good evening'
+        "hey", "how are you", "how are you?", "how is it going", "how is it going?",
+        "what's up?", "how are you?",
+        "hey, how are you?", "what is popping"
+        "good to see you!", "howdy!",
+        "hi, nice to meet you.", "hiya!",
+        "hi", "hi, what's new?",
+        "hey, how's your day?", "hi, how have you been?", "greetings",
+        ]
+    # Random Greetings responses
+    responses = [
+        "Thank you for using our medical chatbot. Please provide the symptoms you're experiencing, and I'll do my best to predict the possible disease.",
+        "Hello! I'm here to help you with medical predictions based on your symptoms. Please describe your symptoms in as much detail as possible.",
+        "Greetings! I am a specialized medical chatbot trained to predict potential diseases based on the symptoms you provide. Kindly list your symptoms explicitly.",
+        "Welcome to the medical chatbot. To assist you accurately, please share your symptoms in explicit detail.",
+        "Hi there! I'm a medical chatbot specialized in analyzing symptoms to suggest possible diseases. Please provide your symptoms explicitly.",
+        "Hey! I'm your medical chatbot. Describe your symptoms with as much detail as you can, and I'll generate potential disease predictions.",
+        "How can I assist you today? I'm a medical chatbot trained to predict diseases based on symptoms. Please be explicit while describing your symptoms.",
+        "Hello! I'm a medical chatbot capable of predicting diseases based on the symptoms you provide. Your explicit symptom description will help me assist you better.",
+        "Greetings! I'm here to help with medical predictions. Describe your symptoms explicitly, and I'll offer insights into potential diseases.",
+        "Hi, I'm the medical chatbot. I've been trained to predict diseases from symptoms. The more explicit you are about your symptoms, the better I can assist you.",
+        "Hi, I specialize in medical predictions based on symptoms. Kindly provide detailed symptoms for accurate disease predictions.",
+        "Hello! I'm a medical chatbot with expertise in predicting diseases from symptoms. Please describe your symptoms explicitly to receive accurate insights.",
+        ]
+    # Random goodbyes
+    goodbyes = [
+        "farewell!",'bye', 'goodbye','good-bye', 'good bye', 'bye', 'thank you', 'later', "take care!",
+        "see you later!", 'see you', 'see ya', 'see-you', 'thanks', 'thank', 'bye bye', 'byebye'
+        "catch you on the flip side!", "adios!",
+        "goodbye for now!", "till we meet again!",
+        "so long!", "hasta la vista!",
+        "bye-bye!", "keep in touch!",
+        "toodles!", "ciao!",
+        "later, gator!", "stay safe and goodbye!",
+        "peace out!", "until next time!", "off I go!",
+        ]
+    # Random Goodbyes responses
+    goodbye_replies = [
+        "Take care of yourself! If you have more questions, don't hesitate to reach out.",
+        "Stay well! Remember, I'm here if you need further medical advice.",
+        "Goodbye for now! Don't hesitate to return if you need more information in the future.",
+        "Wishing you good health ahead! Feel free to come back if you have more concerns.",
+        "Farewell! If you have more symptoms or questions, don't hesitate to consult again.",
+        "Take care and stay informed about your health. Feel free to chat anytime.",
+        "Bye for now! Remember, your well-being is a priority. Don't hesitate to ask if needed.",
+        "Have a great day ahead! If you need medical guidance later on, I'll be here.",
+        "Stay well and take it easy! Reach out if you need more medical insights.",
+        "Until next time! Prioritize your health and reach out if you need assistance.",
+        "Goodbye! Your health matters. Feel free to return if you have more health-related queries.",
+        "Stay healthy and stay curious about your health! If you need more info, just ask.",
+        "Wishing you wellness on your journey! If you have more questions, I'm here to help.",
+        "Take care and remember, your health is important. Don't hesitate to reach out if needed.",
+        "Goodbye for now! Stay informed and feel free to consult if you require medical advice.",
+        "Stay well and stay proactive about your health! If you have more queries, feel free to ask.",
+        "Farewell! Remember, I'm here whenever you need reliable medical information.",
+        "Bye for now! Stay vigilant about your health and don't hesitate to return if necessary.",
+        "Take care and keep your well-being a priority! Reach out if you have more health questions.",
+        "Wishing you good health ahead! Don't hesitate to chat if you need medical insights.",
+        "Goodbye! Stay well and remember, I'm here to assist you with medical queries.",
+    ]
+
+    # Create couple of if-else statements to capture/mimick peoples's Interaction
+  
+    if message.lower() in greetings:
+      bot_message= random.choice(responses)
+    elif message.lower() in goodbyes:
+      bot_message= random.choice(goodbye_replies)
+    else: 
+      bot_message= random.choice(goodbye_replies)
+    '''
+    else:
+      transform_text= vectorizer.transform([message])
+      transform_text= torch.tensor(transform_text.toarray()).to(torch.float32)
+      model.eval()
+      with torch.inference_mode():
+        y_logits=model(transform_text)
+        pred_prob= torch.argmax(torch.softmax(y_logits, dim=1), dim=1)
+   
+      test_pred= class_names[pred_prob.item()] 
+      bot_message = f' Based on your symptoms, I believe you are having {test_pred} and I would advice you {disease_advice[test_pred]}'
+    chat_history.append((message, bot_message))
+    time.sleep(2)
+    return "", chat_history
+    '''
+  msg.submit(respond, [msg, chatbot], [msg, chatbot])
+  
+
+# Launch the demo
+demo.launch()
+

model.py

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+import torch
+from torch import nn
+
+class RNN_model(nn.Module):
+  def __init__(self):
+    super().__init__()
+
+    self.rnn= nn.RNN(input_size=1080, hidden_size=240,num_layers=1, nonlinearity= 'relu', bias= True)
+    self.output= nn.Linear(in_features=240, out_features=24)
+
+  def forward(self, x):
+    y, hidden= self.rnn(x)
+    #print(y.shape)
+    #print(hidden.shape)
+    x= self.output(y)
+
+    return(x)

nltk_u.py

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+# Import Libraries
+import nltk
+from nltk.tokenize import word_tokenize
+nltk.download('punkt')
+from sklearn.feature_extraction.text import TfidfVectorizer
+from nltk.stem import SnowballStemmer
+stemmer= SnowballStemmer(language= 'english')
+from nltk.corpus import stopwords
+nltk.download('stopwords')
+
+# Tokenize text i.e make all text be in a list format e.g "I am sick" = ['i', 'am', 'sick']
+def tokenize(text):
+  return [stemmer.stem(token) for token in word_tokenize(text)]
+
+# Create stopwords to reduce noise in data
+english_stopwords= stopwords.words('english')
+
+# Create a vectosizer to learn all words in order to convert them into numbers
+def vectorizer():
+    vectorizer= TfidfVectorizer(tokenizer=tokenize,
+                                stop_words=english_stopwords,
+                                )
+    return vectorizer
+

pretrained_symtom_to_disease_model.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d182949722a706bed0e7c6319bb893eccc31f8d2b502d023750e0beafd5da8fe
+size 1294703