Update app.py

app.py

@@ -92,6 +92,8 @@ 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")
+tc_t, tc_m = AutoTokenizer.from_pretrained("EIStakovskii/xlm_roberta_base_multilingual_toxicity_classifier_plus"), AutoModelForSequenceClassification.from_pretrained("EIStakovskii/xlm_roberta_base_multilingual_toxicity_classifier_plus")
+chct_t, chct_m = AutoTokenizer.from_pretrained("cointegrated/rut5-small-chitchat"), AutoModelForSequenceClassification.from_pretrained("cointegrated/rut5-small-chitchat")
 
 ##############
 # ANALYZE DATA API
@@ -103,7 +105,7 @@ def sentimentAnalys():
         if text == "": return {"status": "error", "details": { "error_code": 101, "error_details": "No text provided" }}
         
         inputs = sa_t(text, return_tensors="pt")
-        
+
         # Предсказание тональности текста
         outputs = sa_m(**inputs)
         logits = outputs.logits
@@ -112,6 +114,35 @@ 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/toxicity', methods=['GET', 'POST'])
+def toxicityAnalys():
+    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 = tc_t(text, return_tensors="pt")
+        
+        # Предсказание тональности текста
+        outputs = tc_m(**inputs)
+        logits = outputs.logits
+        predicted_class = logits.argmax(dim=1).item()
+        predicted_sentiment = True if str(tc_m.config.id2label[predicted_class]) == "LABEL_1" else False
+    
+        return {"status": "pass", "toxicity": predicted_sentiment}
+    except Exception as e: return {"status": "error", "details": { "error_code": 123, "error_details": str(e).replace("\n", " | ") }}
+@app.route('/analyzeText/api/v1/chitchat', methods=['GET', 'POST'])
+def chitchatRu():
+    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 = chct_t(text, padding=True, truncation=True, return_tensors="pt")
+        outputs = chct_m(**inputs)
+        predicted_class = outputs.logits.argmax(dim=1).item()
+        answer = chct_t.decode(predicted_class)
+    
+        return {"status": "pass", "answer": answer}
+    except Exception as e: return {"status": "error", "details": { "error_code": 123, "error_details": str(e).replace("\n", " | ") }}
 
 if __name__ == "__main__":
     config = configFile()