fix the device

app.py

@@ -18,12 +18,10 @@ st.markdown("""
             background-color: #0f0f11 !important;
             color: #ffffff !important;
         }
-
         /* Universal text color */
         * {
             color: #e0e0e0 !important;
         }
-
         /* Text area styling */
         .stTextArea textarea {
             background-color: #1e1e22 !important;
@@ -31,12 +29,10 @@ st.markdown("""
             font-size: 16px !important;
             border: 1px solid #444 !important;
         }
-
         textarea:focus, .stTextArea textarea:focus {
             border: 2px solid #89CFF0 !important;
             box-shadow: 0 0 0 0.2rem rgba(137, 207, 240, 0.4);
         }
-
         /* Button styling */
         .stButton>button {
             background-color: #7b2cbf;
@@ -46,28 +42,23 @@ st.markdown("""
             border-radius: 6px;
             padding: 0.5rem 1rem;
         }
-
         .stButton>button:hover {
             background-color: #5a189a;
             color: #add8e6 !important;
         }
-
         /* Sidebar */
         section[data-testid="stSidebar"] {
             background-color: #1e1e22 !important;
         }
-
         /* Header / white band fix */
         header[data-testid="stHeader"] {
             background: transparent !important;
         }
-
         /* Table styling */
         .stTable td, .stTable th {
             color: #f4f4f4 !important;
             border-color: #333 !important;
         }
-
         /* Markdown headers */
         h1, h2, h3, h4 {
             color: #9d4edd !important;
@@ -84,13 +75,10 @@ tokenizer = BartTokenizer.from_pretrained(MODEL_PATH)
 def extract_speakers(dialogue):
     """
     Extracts the names of the first two speakers in a dialogue.
-
     Speaker 1: From the first non-space character to the first colon.
     Speaker 2: From the first newline to the second colon.
-
     Args:
         dialogue (str): The dialogue text containing speaker names and conversation.
-
     Returns:
         tuple: A tuple of (speaker_1, speaker_2) or (None, None) if extraction fails.
     """
@@ -211,10 +199,8 @@ def preprocess_text(text):
     - Converts chat abbreviations to full forms using a chat_words dictionary
     - Normalizes punctuation (e.g., "!!" -> "!", "???" -> "?")
     - Cleans up whitespace around punctuation
-
     Args:
         text (str): The input text string to preprocess.
-
     Returns:
         str: The cleaned and preprocessed text.
     """
@@ -311,4 +297,4 @@ metrics = {
 
 metrics_df = pd.DataFrame(metrics.items(), columns=["Metric", "Value"])
 metrics_df = metrics_df.set_index("Metric")
-st.table(metrics_df)
+st.table(metrics_df)