Update app.py

app.py

@@ -5,13 +5,14 @@ import easyocr
 from PIL import Image
 import numpy as np
 
-# Models and labels (same as before)
-SARCASM_MODEL = "j-hartmann/emotion-english-distilroberta-base"
+# Sarcasm Detection Model
+SARCASM_MODEL_NAME = "j-hartmann/emotion-english-distilroberta-base"
 sarcasm_labels = ["not sarcastic", "sarcastic"]
-sarcasm_tokenizer = AutoTokenizer.from_pretrained(SARCASM_MODEL)
-sarcasm_model = AutoModelForSequenceClassification.from_pretrained(SARCASM_MODEL)
+sarcasm_tokenizer = AutoTokenizer.from_pretrained(SARCASM_MODEL_NAME)
+sarcasm_model = AutoModelForSequenceClassification.from_pretrained(SARCASM_MODEL_NAME)
 
-HATE_MODEL = "cardiffnlp/twitter-roberta-base-hate-multiclass-latest"
+# Hate Speech Model
+HATE_MODEL_NAME = "cardiffnlp/twitter-roberta-base-hate-multiclass-latest"
 hate_labels = [
     "sexism",
     "racism",
@@ -21,14 +22,13 @@ hate_labels = [
     "other",
     "not_hate"
 ]
-hate_tokenizer = AutoTokenizer.from_pretrained(HATE_MODEL)
-hate_model = AutoModelForSequenceClassification.from_pretrained(HATE_MODEL)
+hate_tokenizer = AutoTokenizer.from_pretrained(HATE_MODEL_NAME)
+hate_model = AutoModelForSequenceClassification.from_pretrained(HATE_MODEL_NAME)
 
+# OCR Reader
 reader = easyocr.Reader(['en'], gpu=False)
 
 def extract_text(image):
-    if image is None:
-        return ""
     if isinstance(image, Image.Image):
         image = np.array(image)
     texts = reader.readtext(image, detail=0)
@@ -53,50 +53,47 @@ def classify_hate(text):
         return hate_labels[pred], conf
 
 def respond(chat_history, user_text, user_image):
-    # Combine OCR and text input
     if user_image is not None:
-        extracted = extract_text(user_image)
-        if extracted.strip():
-            input_text = extracted
-        elif user_text.strip():
-            input_text = user_text.strip()
+        extracted_text = extract_text(user_image)
+        if extracted_text.strip():
+            text_to_analyze = extracted_text
+        elif user_text and user_text.strip():
+            text_to_analyze = user_text.strip()
         else:
             chat_history.append(("User", ""))
-            chat_history.append(("Bot", "Please provide text or an image with text."))
+            chat_history.append(("Bot", "Please provide text or an image with readable text."))
             return chat_history, None, None
     else:
-        input_text = user_text.strip()
+        text_to_analyze = user_text.strip()
 
-    sarcasm_label, sarcasm_conf = detect_sarcasm(input_text)
+    sarcasm_label, sarcasm_conf = detect_sarcasm(text_to_analyze)
     if sarcasm_label == "sarcastic":
-        response_text = f"Sarcasm detected (Confidence: {sarcasm_conf:.2f}). Hate speech detection skipped."
-        hate_label = None
+        bot_response = f"Sarcasm detected (Confidence: {sarcasm_conf:.2f}). Hate speech detection skipped."
     else:
-        hate_label, hate_conf = classify_hate(input_text)
-        response_text = (
+        hate_label, hate_conf = classify_hate(text_to_analyze)
+        bot_response = (
             f"Hate Speech Category: {hate_label} (Confidence: {hate_conf:.2f})\n"
-            f"Text analyzed: \"{input_text}\""
+            f"Message: \"{text_to_analyze}\""
         )
-    chat_history.append(("User", input_text))
-    chat_history.append(("Bot", response_text))
+    chat_history.append(("User", text_to_analyze))
+    chat_history.append(("Bot", bot_response))
     return chat_history, None, None
 
 with gr.Blocks() as demo:
-    gr.Markdown("# Cyber Bully Detection System (Chat Interface)")
-    
+    gr.Markdown("# Cyber Bully Detection System")
+
     chat_history = gr.State([])
-    
-    with gr.Row():
-        chatbot = gr.Chatbot()
-    with gr.Row():
-        txt = gr.Textbox(show_label=False, placeholder="Type your message here and press enter")
-        img = gr.Image(label="Upload screenshot (optional)", type="pil")
-    with gr.Row():
-        clear = gr.Button("Clear Chat")
+
+    chatbot = gr.Chatbot()
+    txt = gr.Textbox(show_label=False, placeholder="Type your message here and press Enter")
+    img = gr.Image(source="upload", type="pil", label="Upload Screenshot (optional)")
+    clear_btn = gr.Button("Clear Chat")
 
     txt.submit(respond, [chatbot, txt, img], [chatbot, txt, img])
-    img.submit(respond, [chatbot, txt, img], [chatbot, txt, img])
-    clear.click(lambda: ([], None, None), None, [chatbot, txt, img])
+    # Use a button to submit the image instead of img.submit (Image doesn't support submit)
+    submit_img_btn = gr.Button("Analyze Image")
+    submit_img_btn.click(respond, [chatbot, txt, img], [chatbot, txt, img])
+    clear_btn.click(lambda: ([], None, None), None, [chatbot, txt, img])
 
 if __name__ == "__main__":
     demo.launch()