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.gitignore

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+*.pyc
+__pycache__/
+.env
+.streamlit/
+venv/
+.vscode/

app.py

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+import streamlit as st
+import joblib
+import re
+import string
+
+# Load the trained model and TF-IDF vectorizer
+knn_model = joblib.load('knn_model.joblib')
+tfidf_vectorizer = joblib.load('tfidf_vectorizer.joblib')
+
+# Preprocess the input text (same preprocessing as in the notebook)
+def preprocess_text(text):
+    text = text.lower()  # Convert to lowercase
+    text = re.sub(r'\d+', '', text)  # Remove digits
+    text = text.translate(str.maketrans('', '', string.punctuation))  # Remove punctuation
+    return text
+
+# Prediction function
+def predict_disease(symptom):
+    preprocessed_symptom = preprocess_text(symptom)
+    tfidf_features = tfidf_vectorizer.transform([preprocessed_symptom]).toarray()
+    predicted_disease = knn_model.predict(tfidf_features)
+    return predicted_disease[0]
+
+# Streamlit UI Design
+st.set_page_config(page_title="Disease Prediction App", page_icon="🦠", layout="centered")
+
+# Custom Styling
+st.markdown("""
+    <style>
+    body {
+        background-color: #2E2E2E;
+        color: white;
+        font-family: 'Segoe UI', sans-serif;
+    }
+    .header {
+        font-size: 36px;
+        font-weight: bold;
+        color: #00BFFF;
+        text-align: center;
+        margin-top: 30px;
+        margin-bottom: 15px;
+    }
+    .description {
+        font-size: 16px;
+        color: #dcdcdc;
+        text-align: center;
+        margin-bottom: 20px;
+    }
+    .input-box {
+        background-color: #3E3E3E;
+        border-radius: 8px;
+        padding: 15px;
+        font-size: 16px;
+        font-family: 'Segoe UI', sans-serif;
+        border: none;
+        color: white;
+    }
+    .output {
+        background-color: #5F5F5F;
+        border-radius: 8px;
+        padding: 15px;
+        font-size: 18px;
+        color: #00BFFF;
+        font-weight: bold;
+        text-align: center;
+    }
+    .btn {
+        background-color: #00BFFF;
+        color: white;
+        font-size: 18px;
+        padding: 12px 24px;
+        border-radius: 8px;
+        border: none;
+        cursor: pointer;
+        width: 100%;
+    }
+    .btn:hover {
+        background-color: #008B8B;
+    }
+    footer {
+        margin-top: 40px;
+        text-align: center;
+        font-size: 14px;
+        color: #dcdcdc;
+    }
+    .container {
+        padding: 20px;
+        border-radius: 12px;
+        background-color: #383838;
+        max-width: 500px;
+        margin: auto;
+    }
+    </style>
+""", unsafe_allow_html=True)
+
+# Title and Description
+st.markdown("<div class='header'>🦠 Disease Prediction</div>", unsafe_allow_html=True)
+st.markdown("<div class='description'>Enter your symptoms, and the model will predict the possible disease based on the provided input.</div>", unsafe_allow_html=True)
+
+# Input Box and Prediction Button in a centered container
+with st.container():
+    symptom = st.text_area("Enter symptoms:", height=150, max_chars=500, placeholder="E.g., fever, cough, headache...", key="symptom", label_visibility="collapsed")
+    
+    if st.button("Predict", key="predict_button"):
+        if symptom:
+            predicted_disease = predict_disease(symptom)
+            st.markdown(f"<div class='output'>**Predicted Disease: {predicted_disease}**</div>", unsafe_allow_html=True)
+        else:
+            st.warning("Please enter some symptoms to predict the disease.", icon="⚠️")
+
+# Footer with minimalistic text
+st.markdown("""
+    <footer>
+        <p>Powered by AI | Developed for Final Year Project </p>
+    </footer>
+""", unsafe_allow_html=True)

knn_model.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:300017d936663b7d98f76e629ff46adb1c2e63332b4792b3194cf3d5ffd9de80
+size 11076020

requirements.txt

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+streamlit
+joblib
+scikit-learn
+nltk

tfidf_vectorizer.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:334f1610b76e8b40dd348a6b36a0b9cc7a92775a6e80a934ead330fdcb6a769f
+size 65804