Update app.py

app.py

@@ -1,3 +1,4 @@
+
 import streamlit as st
 import random
 from transformers import pipeline, AutoModelForSequenceClassification, AutoTokenizer
@@ -12,36 +13,14 @@ from docx import Document
 # --- Streamlit Page Configuration ---
 st.set_page_config(page_title="AI & Plagiarism Detection", page_icon="🔍")
 
-# --- Color Themes ---
-THEMES = {
-    "midnight": {
-        "primaryColor": "#262730",
-        "backgroundColor": "#0E0F19",
-        "tileColor": "#404040",
-        "textColor": "#FAFAFA",
-        "welcomeTextColor": "#808080",
-    },
-    "forest": {
-        "primaryColor": "#38761d",
-        "backgroundColor": "#228B22",
-        "tileColor": "#3D59AB",
-        "textColor": "#E0FFFF",
-        "welcomeTextColor": "#E0FFFF",
-    },
-    "beach": {
-        "primaryColor": "#F4D03F",
-        "backgroundColor": "#A1D1E8",
-        "tileColor": "#C3B091",
-        "textColor": "#6A5149",
-        "welcomeTextColor": "#795548",
-    },
-    "sunset": {
-        "primaryColor": "#FFB347",
-        "backgroundColor": "#E07A5F",
-        "tileColor": "#3D405B",
-        "textColor": "#F4F1DE",
-        "welcomeTextColor": "#F2CC8F",
-    },
+# --- ChatGPT Theme ---
+CHATGPT_THEME = {
+    "backgroundColor": "#343541",
+    "textColor": "#D1D5DB",
+    "tileColor": "#444654",
+    "inputAreaColor": "#40414F",
+    "accentColor": "#10a37f",
+    "font": "sans-serif",
 }
 
 # --- Function to Apply Theme ---
@@ -51,10 +30,10 @@ def apply_theme(theme):
             body {{
                 color: {theme["textColor"]};
                 background-color: {theme["backgroundColor"]};
-                font-family: sans-serif;
+                font-family: {theme["font"]};
             }}
             .welcome-text {{
-                color: {theme["welcomeTextColor"]};
+                color: {theme["textColor"]};
                 font-size: 36px;
                 font-weight: bold;
                 text-align: center;
@@ -67,8 +46,13 @@ def apply_theme(theme):
                 border-radius: 5px;
                 margin-top: 20px;
             }}
-            .stSlider > div > div {{
-                color: {theme["textColor"]} !important;
+            .stTextArea textarea {{
+                background-color: {theme["inputAreaColor"]};
+                color: {theme["textColor"]};
+            }}
+            .stFileUploader > div > div:nth-child(1) > div > button {{
+                background-color: {theme["accentColor"]};
+                color: {theme["backgroundColor"]};
             }}
             .stMetricLabel {{
                 color: {theme["textColor"]} !important;
@@ -76,10 +60,6 @@ def apply_theme(theme):
             .stMetricValue {{
                 color: {theme["textColor"]} !important;
             }}
-            .stFileUploader > div > div:nth-child(1) > div > button {{
-                background-color: {theme["primaryColor"]};
-                color: {theme["textColor"]};
-            }}
         </style>
     """, unsafe_allow_html=True)
 
@@ -172,18 +152,24 @@ def plagiarism_check(text_chunks, tokenizer, model):
 
 # --- Main Function ---
 def main():
-    # --- Random Theme Selection ---
-    selected_theme = random.choice(list(THEMES.values()))
-    apply_theme(selected_theme)
+    # --- Apply ChatGPT Theme ---
+    apply_theme(CHATGPT_THEME)
 
     # --- Title and Welcome ---
-    st.markdown("<h1 class='welcome-text'>Welcome to AI & Plagiarism Detection</h1>", unsafe_allow_html=True)
+    st.markdown("<h1 class='welcome-text'>AI & Plagiarism Detection</h1>", unsafe_allow_html=True)
 
-    # --- Tabs for File Upload and Text Input ---
-    tab1, tab2 = st.tabs(["Upload File", "Enter Text"])
+    # --- Input Area: Text Area and File Upload ---
+    input_text = st.text_area("Enter text or attach a document", "", height=200)
+    uploaded_files = st.file_uploader("Attach documents (PDF or DOCX)", type=["pdf", "docx"], accept_multiple_files=True)
 
-    with tab1:
-        uploaded_files = st.file_uploader("Upload files (PDF or DOCX)", type=["pdf", "docx"], accept_multiple_files=True)
+    # --- Load models ---
+    ai_detection_model, tokenizer, plagiarism_model = load_models()
+
+    # --- Process Input ---
+    if input_text or uploaded_files:
+        raw_text = ""
+
+        # --- Process Uploaded Files ---
         if uploaded_files:
             for uploaded_file in uploaded_files:
                 file_size = len(uploaded_file.getvalue())
@@ -193,11 +179,10 @@ def main():
 
                 try:
                     if uploaded_file.type == "application/pdf":
-                        raw_text = extract_text_from_pdf(uploaded_file)
+                        raw_text += extract_text_from_pdf(uploaded_file)
                     elif uploaded_file.type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
-                        raw_text = extract_text_from_docx(uploaded_file)
+                        raw_text += extract_text_from_docx(uploaded_file)
                     else:
-                        raw_text = None
                         st.error(f"{uploaded_file.name}: Unsupported file type")
                         continue
 
@@ -205,16 +190,14 @@ def main():
                     st.error(f"Error processing {uploaded_file.name}: {e}")
                     continue
 
-                if raw_text:
-                    # Split text into manageable chunks
-                    text_chunks = split_text_into_chunks(raw_text, tokenizer)
-                    process_and_display(text_chunks, uploaded_file.name, ai_detection_model, tokenizer, plagiarism_model)
+        # --- Append Manual Text ---
+        raw_text += input_text
+
+        # --- Split text into manageable chunks ---
+        text_chunks = split_text_into_chunks(raw_text, tokenizer)
 
-    with tab2:
-        manual_text = st.text_area("Enter text here", "")
-        if manual_text:
-            text_chunks = split_text_into_chunks(manual_text, tokenizer)
-            process_and_display(text_chunks, "Manual Input", ai_detection_model, tokenizer, plagiarism_model)
+        # --- Process and Display Results ---
+        process_and_display(text_chunks, "Combined Input", ai_detection_model, tokenizer, plagiarism_model)
 
 # --- Helper function to process text and display results ---
 def process_and_display(text_chunks, source_name, ai_detection_model, tokenizer, plagiarism_model):