Update app.py

app.py

@@ -92,7 +92,6 @@ def getBMFull(): return osuApi.getFull(request)
 ###############
 # LOAD MODELS
 sa_t, sa_m = AutoTokenizer.from_pretrained("cardiffnlp/twitter-xlm-roberta-base-sentiment"), AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-xlm-roberta-base-sentiment")
-ld_t, ld_m = AutoTokenizer.from_pretrained("papluca/xlm-roberta-base-language-detection"), AutoModelForSequenceClassification.from_pretrained("papluca/xlm-roberta-base-language-detection")
 
 ##############
 # ANALYZE DATA API
@@ -114,22 +113,6 @@ def sentimentAnalys():
         return {"status": "pass", "predicted_sentiment": predicted_sentiment}
     except Exception as e: return {"status": "error", "details": { "error_code": 123, "error_details": str(e).replace("\n", " | ") }}
 
-@app.route('/analyzeText/api/v1/detectLang', methods=['GET', 'POST'])
-def langDetect():
-    try:
-        text = request.form.get('text') or request.args.get('text') or request.values.get('text') or ""
-        if text == "": return {"status": "error", "details": { "error_code": 101, "error_details": "No text provided" }}
-            
-        inputs = ld_t(text, return_tensors="pt")  
-        
-        outputs = ld_m(**inputs)
-        logits = outputs.logits
-        predicted_language_index = logits.argmax(dim=1).item()
-        predicted_language = ld_m.config.id2label[predicted_language_index]
-        
-        return {"status": "pass", "predicted_language": predicted_language}
-    except Exception as e: return {"status": "error", "details": { "error_code": 123, "error_details": str(e).replace("\n", " | ") }}
-
 if __name__ == "__main__":
     config = configFile()
     with open(config['config-path'], "w") as outfile: