Update app/main.py

app/main.py

@@ -4,27 +4,18 @@ from transformers import pipeline, AutoTokenizer
 from glin_profanity import Filter
 import re
 
-# 1. Toxicity classifier
+# 1. Models
 toxicity_pipe = pipeline("text-classification", model="textdetox/twitter-xlmr-toxicity-classifier")
-
-# 2. UPGRADED: Use a highly capable Chat Model (Phi-3)
 model_id = "microsoft/Phi-3-mini-4k-instruct"
-
-# --- ADD trust_remote_code=True HERE ---
 tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
-llm_pipe = pipeline(
-    "text-generation", 
-    model=model_id, 
-    tokenizer=tokenizer, 
-    trust_remote_code=True # <--- THE FIX
-)
-
+llm_pipe = pipeline("text-generation", model=model_id, tokenizer=tokenizer, trust_remote_code=True)
 profanity_filter = Filter({"languages": ["english", "spanish", "french"], "replace_with": "***"})
 
 app = FastAPI(title="Multilingual Moderation API")
 
+# 2. Request Model - THIS IS THE CRITICAL PART
 class TextRequest(BaseModel):
-    text: str
+    text: str  # <--- It MUST be 'text', not 'data'
 
 class ModerationResponse(BaseModel):
     original_text: str
@@ -41,7 +32,7 @@ threat_pattern = re.compile("|".join(THREAT_KEYWORDS), re.IGNORECASE)
 
 @app.post("/moderate", response_model=ModerationResponse)
 async def moderate_text(request: TextRequest):
-    text = request.text
+    text = request.text # Using 'text' correctly
     
     profanity_result = profanity_filter.check_profanity(text)
     tox_result = toxicity_pipe(text)[0]
@@ -64,7 +55,6 @@ async def moderate_text(request: TextRequest):
         
         prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
         outputs = llm_pipe(prompt, max_new_tokens=200, do_sample=True, temperature=0.7)
-        
         generated_text = outputs[0]['generated_text'][len(prompt):].strip()
         
         lines = generated_text.split('\n')
@@ -78,7 +68,6 @@ async def moderate_text(request: TextRequest):
                     rewritten.append(clean_line)
         
         rewritten = list(dict.fromkeys(rewritten))[:5]
-
         if not rewritten:
             rewritten = ["[AI could not generate a rewrite, please revise manually]"]