Update app.py

app.py

@@ -1,11 +1,10 @@
 import gradio as gr
 import torch
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from transformers.pipelines import pipeline
 from sentence_transformers import SentenceTransformer, util
 import numpy as np
-import requests
 import gradio.themes as grthemes
-import config
 import random
 import re
 
@@ -23,6 +22,12 @@ paraphrase_model = paraphrase_model.to(device)
 # ----------------------
 similarity_model = SentenceTransformer('all-MiniLM-L6-v2')
 
+# ----------------------
+# Local AI Detector (desklib/ai-text-detector-v1.01)
+# ----------------------
+AI_DETECTOR_MODEL = "desklib/ai-text-detector-v1.01"
+ai_detector = pipeline("text-classification", model=AI_DETECTOR_MODEL, device=0 if torch.cuda.is_available() else -1)
+
 # ----------------------
 # Prompt Variations for Humanization
 # ----------------------
@@ -41,7 +46,6 @@ PROMPT_VARIANTS = [
 # Sentence Splitter
 # ----------------------
 def split_sentences(text):
-    # Simple sentence splitter (can be improved for edge cases)
     sentences = re.split(r'(?<=[.!?])\s+', text.strip())
     return [s for s in sentences if s]
 
@@ -49,7 +53,6 @@ def split_sentences(text):
 # Light Post-Processing
 # ----------------------
 def postprocess_text(text):
-    # Add contractions, simple idioms, and vary sentence length a bit
     contractions = {
         "do not": "don't", "cannot": "can't", "will not": "won't", "I am": "I'm",
         "is not": "isn't", "are not": "aren't", "did not": "didn't", "it is": "it's",
@@ -57,7 +60,6 @@ def postprocess_text(text):
     }
     for k, v in contractions.items():
         text = re.sub(rf'\b{k}\b', v, text, flags=re.IGNORECASE)
-    # Add a simple idiom randomly
     idioms = [
         "at the end of the day", "to be honest", "as a matter of fact", "for what it's worth",
         "in a nutshell", "the bottom line is", "all things considered"
@@ -107,32 +109,20 @@ def semantic_similarity(text1, text2):
     return sim
 
 # ----------------------
-# Real AI Detection (Winston AI API)
+# Local AI Detection Function
 # ----------------------
 def check_ai_score(text):
-    api_key = config.WINSTON_AI_API_KEY
-    api_url = config.WINSTON_AI_API_URL
-    if not api_key:
-        return None, "No API key set. Please add your Winston AI API key to config.py."
-    headers = {
-        "Authorization": f"Bearer {api_key}",
-        "Content-Type": "application/json"
-    }
-    data = {"text": text, "sentences": False}
     try:
-        response = requests.post(api_url, headers=headers, json=data, timeout=30)
-        if response.status_code == 200:
-            result = response.json()
-            score = result.get("score", None)
-            if score is not None:
-                ai_prob = 1.0 - (score / 100.0)
-                return ai_prob, None
-            else:
-                return None, "No score in Winston AI response."
-        else:
-            return None, f"Winston AI error: {response.status_code} {response.text}"
+        result = ai_detector(text)
+        for r in result:
+            # LABEL_1 = AI, LABEL_0 = Human
+            if r['label'] in ['LABEL_1', 'Fake']:
+                return r['score'], None
+            elif r['label'] in ['LABEL_0', 'Real']:
+                return 1.0 - r['score'], None
+        return 0.5, None  # fallback
     except Exception as e:
-        return None, f"Winston AI exception: {str(e)}"
+        return None, f"AI detection error: {str(e)}"
 
 # ----------------------
 # Humanization Score & Rating