Create app.py

app.py

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+import gradio as gr
+import joblib
+import pandas as pd
+
+# Cargar el modelo
+model = joblib.load("classification_model.pkl")
+
+def predict_text(title, abstract):
+    text = f"{title} {abstract}"
+    pred = model.predict([text])[0]
+    return pred
+
+def predict_file(file):
+    df = pd.read_csv(file, sep=";")
+    df["Prediction"] = model.predict(df["title"] + " " + df["abstract"])
+    return df
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 🩺 Medical Text Classifier")
+
+    with gr.Tab("Texto individual"):
+        title = gr.Textbox(label="Título")
+        abstract = gr.Textbox(label="Abstract")
+        output = gr.Textbox(label="Predicción")
+        btn = gr.Button("Clasificar")
+        btn.click(predict_text, inputs=[title, abstract], outputs=output)
+
+    with gr.Tab("Archivo CSV"):
+        file_input = gr.File(label="Subir CSV", file_types=[".csv"])
+        file_output = gr.Dataframe()
+        file_input.change(predict_file, inputs=file_input, outputs=file_output)
+
+demo.launch()