Update app.py

app.py

@@ -2,6 +2,8 @@ import gradio as gr
 import os
 from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
 import json
+import socket
+from datetime import datetime
 
 access_token = os.environ['ACCES_TOKEN']
 
@@ -20,8 +22,19 @@ classifier = pipeline("text-classification", tokenizer=tokenizer, model=model, m
 adibideak = json.load(open("./Adibideak.json", "r"))
 
 def prozesatu(Testua, request: gr.Request):
-    if Testua[-3:]=="...":
-        Testua = prozesatu.adibideak[Testua]
+    client_ip = request.client.host
+    local_ip = socket.gethostbyname(socket.gethostbyname(""))
+    headers = request.kwargs['headers']
+    if headers and 'x-forwarded-for' in headers:
+        x_forwarded_for = headers['x-forwarded-for']
+        client_ip = x_forwarded_for.split(' ')[0] if x_forwarded_for else ""
+
+    f = open("Erabiltzaileak.txt", "a")
+    
+    f.write(f'Erabiltzailea: {client_ip}. Eguna eta ordua: {now}.\n')
+
+    f.close()
+    
     prediction = prozesatu.classifier(Testua)[0]
     if prediction["label"]=="GAI":
         return {"Gai":prediction["score"], "Ez gai": 1-prediction["score"]}