Update app.py

app.py

@@ -9,6 +9,13 @@ from nltk.sentiment import SentimentIntensityAnalyzer
 import nltk
 from collections import Counter
 import uvicorn
+import requests
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+HF_API_TOKEN = os.getenv("HF_API_TOKEN")
 
 # Download NLTK resources
 try:
@@ -27,12 +34,12 @@ app.add_middleware(
     allow_credentials=True,
     allow_methods=["*"],  # Allows all methods
     allow_headers=["*"],  # Allows all headers
-)
+) 
 
 humanize_pipe = None  # Default to None before trying to load
 
 try:
-    humanize_pipe = pipeline("text2text-generation", model="danibor/flan-t5-base-humanizer")
+    # humanize_pipe = pipeline("text2text-generation", model="danibor/flan-t5-base-humanizer")
     print("Humanization model loaded successfully!")
     
     # Load spaCy model
@@ -74,12 +81,11 @@ async def humanize_text(request: TextRequest):
     input_text = request.text
     
     try:
-        # Generate humanized text
-        if humanize_pipe is None:
-            raise HTTPException(status_code=500, detail="Humanization model is not loaded.")
+        API_URL = "https://api-inference.huggingface.co/models/danibor/flan-t5-base-humanizer"
+        headers = {"Authorization": f"Bearer {HF_API_TOKEN}"}
 
-        result = humanize_pipe(input_text, max_length=500, do_sample=True)
-        humanized_text = result[0]['generated_text']
+        response = requests.post(API_URL, headers=headers, json={"inputs": text})
+        humanized_text = response.json()[0]["generated_text"]
         
         # Get the differences
         diff = get_diff(input_text, humanized_text)