Update app.py

app.py

@@ -1,4 +1,5 @@
 import os
+import numpy as np
 import tensorflow as tf
 from tensorflow import keras
 import gradio as gr
@@ -11,14 +12,16 @@ model_path = 'doctor_ai_model.h5'  # Change this to your actual model path
 model = keras.models.load_model(model_path)
 
 def chatbot(input_text):
-    # Here, preprocess the input_text if needed.
-    # If your model requires tokenization, do that instead.
-    # For example:
+    # Preprocess input_text if necessary
+    # For example, you may need to tokenize the input or convert it to a sequence
     # input_tensor = your_tokenizer.texts_to_sequences([input_text])  
     # input_tensor = tf.keras.preprocessing.sequence.pad_sequences(input_tensor)
 
-    # Assuming your model expects string input or specific preprocessing
-    response = model.predict([input_text])  # Adjust based on your model's expected input
+    # Assuming your model accepts a 2D array (batch size, features)
+    input_tensor = np.array([input_text])  # Convert list to numpy array
+
+    # Make a prediction
+    response = model.predict(input_tensor)  # Adjust based on your model's expected input
 
     return response[0]  # Adjust based on your model output