Komal-patra commited on
Commit
85bca36
·
verified ·
1 Parent(s): d99d01c
Files changed (1) hide show
  1. app.py +18 -5
app.py CHANGED
@@ -6,14 +6,17 @@ from peft import PeftModel, PeftConfig
6
 
7
  # Hugging Face login
8
  token = os.environ.get("token")
9
- login(token)
10
- print("Login is successful")
 
 
 
11
 
12
  # Model and tokenizer setup
13
  MODEL_NAME = "google/flan-t5-base"
14
- tokenizer = T5Tokenizer.from_pretrained(MODEL_NAME, token=token)
15
  config = PeftConfig.from_pretrained("Komal-patra/results")
16
- base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base")
17
  model = PeftModel.from_pretrained(base_model, "Komal-patra/results")
18
 
19
  # Text generation function
@@ -50,6 +53,14 @@ span.md.svelte-8tpqd2.chatbot.prose p {
50
  .gradio-container {
51
  background: #1c1c1c; /* Dark background */
52
  color: white; /* Light text color */
 
 
 
 
 
 
 
 
53
  }
54
  /* RED (Hex: #DB1616) for action buttons and links only */
55
  .clear-btn {
@@ -94,9 +105,11 @@ with gr.Blocks(css=custom_css) as demo:
94
  submit_button = gr.Button("Submit", elem_classes="submit-btn")
95
  clear = gr.Button("Clear", elem_classes="clear-btn")
96
 
 
97
  def user(user_message, history):
98
  return "", history + [[user_message, None]]
99
 
 
100
  def bot(history):
101
  if len(history) == 1: # Check if it's the first interaction
102
  bot_message = "Hi there! How can I help you today?"
@@ -116,4 +129,4 @@ with gr.Blocks(css=custom_css) as demo:
116
  )
117
  clear.click(lambda: None, None, chatbot, queue=False)
118
 
119
- demo.launch()
 
6
 
7
  # Hugging Face login
8
  token = os.environ.get("token")
9
+ if token:
10
+ login(token)
11
+ print("Login is successful")
12
+ else:
13
+ print("Token not found. Please set your token in the environment variables.")
14
 
15
  # Model and tokenizer setup
16
  MODEL_NAME = "google/flan-t5-base"
17
+ tokenizer = T5Tokenizer.from_pretrained(MODEL_NAME, use_auth_token=token)
18
  config = PeftConfig.from_pretrained("Komal-patra/results")
19
+ base_model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)
20
  model = PeftModel.from_pretrained(base_model, "Komal-patra/results")
21
 
22
  # Text generation function
 
53
  .gradio-container {
54
  background: #1c1c1c; /* Dark background */
55
  color: white; /* Light text color */
56
+ height: 100vh; /* Full viewport height */
57
+ display: flex;
58
+ flex-direction: column;
59
+ }
60
+ /* Chatbot messages container */
61
+ .svelte-1s78gfg {
62
+ flex-grow: 1; /* Allow it to grow and take available space */
63
+ overflow-y: auto; /* Enable vertical scrolling */
64
  }
65
  /* RED (Hex: #DB1616) for action buttons and links only */
66
  .clear-btn {
 
105
  submit_button = gr.Button("Submit", elem_classes="submit-btn")
106
  clear = gr.Button("Clear", elem_classes="clear-btn")
107
 
108
+ # Function to handle user input
109
  def user(user_message, history):
110
  return "", history + [[user_message, None]]
111
 
112
+ # Function to handle bot response
113
  def bot(history):
114
  if len(history) == 1: # Check if it's the first interaction
115
  bot_message = "Hi there! How can I help you today?"
 
129
  )
130
  clear.click(lambda: None, None, chatbot, queue=False)
131
 
132
+ demo.launch(share=True)