Create app.py

app.py

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+import gradio as gr
+import pandas as pd
+
+# Load the dataset from the uploaded CSV file
+df = pd.read_csv("thyroid_disease_data.csv")
+
+# Define the function to classify the text
+def classify_thyroid_disease(text):
+    # Search the dataset for a matching symptom text (basic string matching)
+    result = df[df['text'].str.contains(text, case=False, na=False)]
+    
+    # Return a diagnosis based on the found label
+    if not result.empty:
+        label = result['label'].iloc[0]
+        diagnosis = "Hypothyroidism" if label == 0 else "Hyperthyroidism"
+        return diagnosis
+    return "No matching diagnosis found."
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=classify_thyroid_disease,
+    inputs="text",  # User input will be a text field
+    outputs="text"  # Output will be a text diagnosis
+)
+
+# Launch the Gradio app
+interface.launch()