Update app.py

app.py

@@ -5,27 +5,27 @@ import easyocr
 from PIL import Image
 import numpy as np
 
-# Sarcasm Detection Model (public)
+# Sarcasm Model
 SARCASM_MODEL_NAME = "j-hartmann/emotion-english-distilroberta-base"
 sarcasm_labels = ["not sarcastic", "sarcastic"]
 sarcasm_tokenizer = AutoTokenizer.from_pretrained(SARCASM_MODEL_NAME)
 sarcasm_model = AutoModelForSequenceClassification.from_pretrained(SARCASM_MODEL_NAME)
 
-# Hate Speech Model - DeBERTa fine-tuned (replace with your own model)
-HATE_MODEL_NAME = "your-username/deberta-hate-speech-custom"
+# Hate Speech Model (RoBERTa multiclass)
+HATE_MODEL_NAME = "cardiffnlp/twitter-roberta-base-hate-multiclass-latest"
 hate_labels = [
-    "abusive_language",
-    "harassment",
-    "threat",
-    "racism",
     "sexism",
-    "religious_hate",
+    "racism",
+    "disability",
+    "sexual_orientation",
+    "religion",
+    "other",
     "not_hate"
 ]
 hate_tokenizer = AutoTokenizer.from_pretrained(HATE_MODEL_NAME)
 hate_model = AutoModelForSequenceClassification.from_pretrained(HATE_MODEL_NAME)
 
-# OCR
+# OCR Reader
 reader = easyocr.Reader(['en'], gpu=False)
 
 def extract_text(image):
@@ -52,38 +52,52 @@ def classify_hate(text):
         confidence = float(probs[0][pred])
         return hate_labels[pred], confidence
 
-def pipeline(image=None, text=None):
+
+def chatbot(conversation, user_message, image=None):
+    # Process image first if available
     if image is not None:
-        input_text = extract_text(image)
-        if not input_text.strip():
-            return "No text found in image.", None
-    elif text and text.strip():
-        input_text = text
+        extracted_text = extract_text(image)
+        if not extracted_text.strip():
+            response = "No text found in the uploaded image."
+            conversation.append(("User", user_message))
+            conversation.append(("Cyber Bully Bot", response))
+            return conversation, None, None
+        text = extracted_text
+        display_input = f"[Extracted from image] {text}"
     else:
-        return "Please provide text or upload an image.", None
+        text = user_message.strip()
+        display_input = text
 
-    sarcasm_label, sarcasm_conf = detect_sarcasm(input_text)
+    # Sarcasm detection
+    sarcasm_label, sarcasm_conf = detect_sarcasm(text)
     if sarcasm_label == "sarcastic":
-        return f"Text detected as SARCASTIC (Confidence: {sarcasm_conf:.2f}). Hate speech classification skipped.", sarcasm_label
+        response = f"Text detected as SARCASTIC (Confidence: {sarcasm_conf:.2f}). Hate speech classification skipped."
+        conversation.append(("User", display_input))
+        conversation.append(("Cyber Bully Bot", response))
+        return conversation, None, None
 
-    hate_label, hate_conf = classify_hate(input_text)
-    return (
-        f"Input Text: {input_text}\nHate Speech Category: {hate_label} (Confidence: {hate_conf:.2f})\nSarcasm: {sarcasm_label} (Confidence: {sarcasm_conf:.2f})",
-        hate_label
+    # Hate speech classification
+    hate_label, hate_conf = classify_hate(text)
+    response = (
+        f"Hate Speech Category: {hate_label} (Confidence: {hate_conf:.2f})\n"
+        f"Sarcasm: {sarcasm_label} (Confidence: {sarcasm_conf:.2f})"
     )
+    conversation.append(("User", display_input))
+    conversation.append(("Cyber Bully Bot", response))
+    return conversation, None, None
 
-iface = gr.Interface(
-    fn=pipeline,
-    inputs=[
-        gr.Image(type="pil", label="Upload Screenshot (optional)"),
-        gr.Textbox(lines=3, placeholder="Or, type/paste text here")
-    ],
-    outputs=[
-        gr.Textbox(label="Result"),
-        gr.Label(num_top_classes=len(hate_labels), label="Hate Speech Class")
-    ],
+default_conversation = []
+
+iface = gr.ChatInterface(
+    fn=chatbot,
     title="Cyber Bully Detection System",
-    description="Detects sarcasm first; if no sarcasm detected, classifies hate speech into abusive language, harassment, threat, racism, sexism, religious hate, or no hate."
+    description="Upload images or enter text. Bot detects sarcasm first, then classifies hate speech categories.",
+)
+
+# Add an image upload component beside text input
+iface.add_component(
+    gr.Image(source="upload", label="Upload Screenshot (optional)", interactive=True),
+    insert_before=iface.input_components[0]
 )
 
 if __name__ == "__main__":