Update app.py

app.py

@@ -72,11 +72,8 @@ class TextHumanizer:
         }
 
     def detect_ai_text(self, text: str) -> float:
-        """
-        Detect if text is AI-generated and return confidence score
-        """
+        """Detect if text is AI-generated and return confidence score"""
         try:
-            # Split long text into sentences and analyze each chunk
             sentences = sent_tokenize(text)
             chunks = [' '.join(sentences[i:i+5]) for i in range(0, len(sentences), 5)]
             
@@ -93,10 +90,7 @@ class TextHumanizer:
             return 0.0
 
     def add_human_variations(self, text: str) -> str:
-        """
-        Add human-like variations to text
-        """
-        # Add occasional filler words
+        """Add human-like variations to text"""
         fillers = ["well", "you know", "actually", "basically", "I mean"]
         
         try:
@@ -106,11 +100,10 @@ class TextHumanizer:
             sentences = text.split('.')
             
         for i in range(len(sentences)):
-            if random.random() < 0.3:  # 30% chance to add filler
+            if random.random() < 0.3:
                 filler = random.choice(fillers)
                 sentences[i] = f"{filler}, {sentences[i].lower()}"
         
-        # Add minor grammatical variations
         text = ' '.join(sentences)
         text = text.replace(" can not ", " can't ")
         text = text.replace(" do not ", " don't ")
@@ -124,25 +117,19 @@ class TextHumanizer:
         translate_to: Optional[str] = None,
         max_retries: int = 3
     ) -> str:
-        """
-        Main function to humanize text with error handling and retries
-        """
+        """Main humanization function with error handling"""
         try:
-            # Verify NLTK is properly initialized
             nltk.data.find('tokenizers/punkt')
             
-            # Check if text is likely AI-generated
             ai_score = self.detect_ai_text(text)
             logger.info(f"AI detection score: {ai_score}")
             
-            if ai_score < 0.7:  # If text already seems human-like
+            if ai_score < 0.7:
                 logger.info("Text appears human-written, making minor adjustments")
                 output = self.add_human_variations(text)
             else:
-                # Select random prompt variation for the chosen tone
                 prompt = random.choice(self.tone_prompts[tone]).format(text=text)
                 
-                # Try generation with retries
                 for attempt in range(max_retries):
                     try:
                         output = self.humanizer(
@@ -153,15 +140,13 @@ class TextHumanizer:
                             top_p=0.9
                         )[0]['generated_text']
                         
-                        # Add human variations
                         output = self.add_human_variations(output)
-                        
-                        # Verify the output is more human-like
                         new_ai_score = self.detect_ai_text(output)
+                        
                         if new_ai_score < ai_score:
                             break
                         elif attempt < max_retries - 1:
-                            logger.warning(f"Attempt {attempt + 1}: Output still seems AI-like, retrying...")
+                            logger.warning(f"Attempt {attempt + 1}: Retrying...")
                             time.sleep(1)
                     except Exception as e:
                         if attempt < max_retries - 1:
@@ -170,7 +155,6 @@ class TextHumanizer:
                         else:
                             raise
             
-            # Handle translation if requested
             if translate_to and translate_to != "None":
                 lang_code = translate_to.split(" ")[0]
                 output = self.translator.translate(output, destination_language=lang_code).result
@@ -184,8 +168,20 @@ class TextHumanizer:
 def create_interface():
     humanizer = TextHumanizer()
     
-    def process_text(text: str, tone: str, translate_to: str) -> str:
-        return humanizer.humanize_text(text, tone, translate_to)
+    def process_text(text: str, tone: str, translate_to: str) -> Dict:
+        try:
+            processed = humanizer.humanize_text(text, tone, translate_to)
+            return {
+                "data": [processed],
+                "success": True,
+                "error": None
+            }
+        except Exception as e:
+            return {
+                "data": [],
+                "success": False,
+                "error": str(e)
+            }
     
     iface = gr.Interface(
         fn=process_text,
@@ -196,7 +192,7 @@ def create_interface():
                 lines=5
             ),
             gr.Dropdown(
-                choices=list(humanizer.tone_prompts.keys()),
+                choices=list(humanizer.tone_prompts.keys()),  # Restored dynamic tones
                 label="Writing Style",
                 value="Casual",
                 info="Select the desired writing style for the output"
@@ -216,7 +212,7 @@ def create_interface():
                 info="Optional: translate the output to another language"
             )
         ],
-        outputs=gr.Textbox(label="Humanized Output", lines=5),
+        outputs=gr.JSON(label="API Response"),
         title="AI Text Humanizer",
         description="Convert AI-generated text into more natural, human-like writing",
         examples=[
@@ -227,16 +223,16 @@ def create_interface():
              "Business",
              "es (Spanish)"]
         ],
-        cache_examples=True
+        allow_flagging="never"
     )
-    return iface
-
-if __name__ == "__main__":
-    # Set up thread pool for handling multiple requests
-    interface = create_interface()
-    interface.queue()
-    interface.launch(
+    
+    iface.launch(
         server_name="0.0.0.0",
         server_port=7860,
-        share=True
-    )
+        share=True,
+        cors_allowed_origins=["*"],
+        allowed_paths=["*"]
+    )
+
+if __name__ == "__main__":
+    create_interface()