Update main.py

main.py

@@ -1,11 +1,14 @@
 import os
-from fastapi import FastAPI, HTTPException
+from fastapi import FastAPI
 from pydantic import BaseModel
 from transformers import pipeline
-import langdetect
+from langdetect import detect, DetectorFactory
 
-# Set custom cache directory to avoid permission issues
-os.environ["TRANSFORMERS_CACHE"] = "/app/cache"
+# Ensure consistent language detection results
+DetectorFactory.seed = 0
+
+# Set HF cache directory instead of TRANSFORMERS_CACHE
+os.environ["HF_HOME"] = "/app/cache"
 
 app = FastAPI()
 
@@ -22,9 +25,9 @@ class SentimentResponse(BaseModel):
     sentiment: str
     confidence_score: float
 
-def detect_language(text: str) -> str:
+def detect_language(text):
     try:
-        return langdetect.detect(text)
+        return detect(text)
     except:
         return "unknown"
 
@@ -34,24 +37,18 @@ def home():
 
 @app.post("/analyze/", response_model=SentimentResponse)
 def analyze_sentiment(request: SentimentRequest):
-    if not request.text:
-        raise HTTPException(status_code=400, detail="No text provided")
-    
     text = request.text
     language = detect_language(text)
-    
+
     # Choose the appropriate model based on language
     if language == "en":
         result = english_model(text)
     else:
         result = multilingual_model(text)
-    
-    sentiment = result[0]["label"].lower()
-    score = result[0]["score"]
-    
+
     return SentimentResponse(
         original_text=text,
         language_detected=language,
-        sentiment=sentiment,
-        confidence_score=score
+        sentiment=result[0]["label"].lower(),
+        confidence_score=result[0]["score"],
     )