Update app.py

app.py

@@ -1,6 +1,4 @@
 import nltk
-nltk.download('punkt')
-from nltk.stem.lancaster import LancasterStemmer
 import numpy as np
 import tflearn
 import tensorflow
@@ -9,12 +7,10 @@ import json
 import pickle
 import gradio as gr
 from nltk.tokenize import word_tokenize
+from nltk.stem.lancaster import LancasterStemmer
 
 # Ensure necessary NLTK resources are downloaded
-try:
-    nltk.data.find('tokenizers/punkt')
-except LookupError:
-    nltk.download('punkt')
+nltk.download('punkt')
 
 # Initialize the stemmer
 stemmer = LancasterStemmer()
@@ -45,12 +41,12 @@ model = tflearn.DNN(net)
 try:
     model.load("MentalHealthChatBotmodel.tflearn")
 except FileNotFoundError:
-    print("Error: Trained model file not found. Ensure 'MentalHealthChatBotmodel.tflearn' exists.")
+    raise FileNotFoundError("Error: Trained model file 'MentalHealthChatBotmodel.tflearn' not found.")
 
 # Function to process user input into a bag-of-words format
 def bag_of_words(s, words):
     bag = [0 for _ in range(len(words))]
-    s_words = word_tokenize(s)  # Replaced nltk.word_tokenize(s)
+    s_words = word_tokenize(s)
     s_words = [stemmer.stem(word.lower()) for word in s_words if word.lower() in words]
     for se in s_words:
         for i, w in enumerate(words):
@@ -86,67 +82,12 @@ def chat(message, history):
 
 # Gradio interface
 chatbot = gr.Chatbot(label="Chat")
-css = """
-footer {display:none !important}
-.output-markdown{display:none !important}
-.gr-button-primary {
-    z-index: 14;
-    height: 43px;
-    width: 130px;
-    left: 0px;
-    top: 0px;
-    padding: 0px;
-    cursor: pointer !important; 
-    background: none rgb(17, 20, 45) !important;
-    border: none !important;
-    text-align: center !important;
-    font-family: Poppins !important;
-    font-size: 14px !important;
-    font-weight: 500 !important;
-    color: rgb(255, 255, 255) !important;
-    line-height: 1 !important;
-    border-radius: 12px !important;
-    transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important;
-    box-shadow: none !important;
-}
-.gr-button-primary:hover{
-    z-index: 14;
-    height: 43px;
-    width: 130px;
-    left: 0px;
-    top: 0px;
-    padding: 0px;
-    cursor: pointer !important;
-    background: none rgb(37, 56, 133) !important;
-    border: none !important;
-    text-align: center !important;
-    font-family: Poppins !important;
-    font-size: 14px !important;
-    font-weight: 500 !important;
-    color: rgb(255, 255, 255) !important;
-    line-height: 1 !important;
-    border-radius: 12px !important;
-    transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important;
-    box-shadow: rgb(0 0 0 / 23%) 0px 1px 7px 0px !important;
-}
-.hover\:bg-orange-50:hover {
-    --tw-bg-opacity: 1 !important;
-    background-color: rgb(229,225,255) !important;
-}
-div[data-testid="user"] {
-  background-color: #253885 !important;
-}
-.h-\[40vh\]{
-height: 70vh !important;
-}
-"""
 demo = gr.Interface(
     chat,
     [gr.Textbox(lines=1, label="Message"), "state"],
     [chatbot, "state"],
     allow_flagging="never",
-    title="Mental Health Bot | Data Science Dojo",
-    css=css
+    title="Wellbeing for All, ** I am your Best Friend **",
 )
 
 # Launch Gradio interface