updated code to resolve import error

app.py

@@ -1,11 +1,10 @@
 import nltk
 nltk.download('punkt')
 
-import nltk
 from nltk.stem.lancaster import LancasterStemmer
 import numpy as np
-import tflearn
-import tensorflow
+import tensorflow as tf
+from tensorflow.keras.models import load_model
 import random
 import json
 import pandas as pd
@@ -18,18 +17,9 @@ with open("intents.json") as file:
     data = json.load(file)
 
 with open("data.pickle", "rb") as f:
-  words, labels, training, output = pickle.load(f)
-
-net = tflearn.input_data(shape=[None, len(training[0])])
-net = tflearn.fully_connected(net, 8)
-net = tflearn.fully_connected(net, 8)
-net = tflearn.fully_connected(net, len(output[0]), activation="softmax")
-net = tflearn.regression(net)
-
-model = tflearn.DNN(net)
-model.load("MentalHealthChatBotmodel.tflearn")
-# print('model loaded successfully')
+    words, labels, training, output = pickle.load(f)
 
+model = load_model("MentalHealthChatBotmodel.tflearn")
 
 def bag_of_words(s, words):
     bag = [0 for _ in range(len(words))]
@@ -44,25 +34,22 @@ def bag_of_words(s, words):
             
     return np.array(bag)
 
-
 def chat(message, history):
     history = history or []
     message = message.lower()
-    results = model.predict([bag_of_words(message, words)])
+    results = model.predict(np.array([bag_of_words(message, words)]))
     results_index = np.argmax(results)
     tag = labels[results_index]
 
     for tg in data["intents"]:
-      if tg['tag'] == tag:
-        responses = tg['responses']
+        if tg['tag'] == tag:
+            responses = tg['responses']
+            response = random.choice(responses)
 
-        # print(random.choice(responses))
-        response = random.choice(responses)
-  
     history.append((message, response))
     return history, history
 
-chatbot = gr.Chatbot(label="Chat")
+chatbot = gr.Chatbot(chat)
 css = """
 footer {display:none !important}
 .output-markdown{display:none !important}