Fix for web based model loading

aiserver.py

@@ -53,6 +53,7 @@ from utils import debounce
 import utils
 import structures
 import torch
+from transformers import StoppingCriteria, GPT2TokenizerFast, GPT2LMHeadModel, GPTNeoForCausalLM, GPTNeoModel, AutoModelForCausalLM, AutoTokenizer
 
 
 if lupa.LUA_VERSION[:2] != (5, 4):
@@ -321,6 +322,12 @@ class vars:
 
 utils.vars = vars
 
+class Send_to_socketio(object):
+    def write(self, bar):
+        print(bar, end="")
+        time.sleep(0.01)
+        emit('from_server', {'cmd': 'model_load_status', 'data': bar}, broadcast=True)
+                                
 # Set logging level to reduce chatter from Flask
 import logging
 log = logging.getLogger('werkzeug')
@@ -986,6 +993,10 @@ def load_model(use_gpu=True, key='', gpu_layers=None, initial_load=False):
     vars.noai = False
     if not initial_load:
         set_aibusy(True)
+        if vars.model != 'ReadOnly':
+            emit('from_server', {'cmd': 'model_load_status', 'data': "Loading {}".format(vars.model)}, broadcast=True)
+            #Have to add a sleep so the server will send the emit for some reason
+            time.sleep(0.1)
     if gpu_layers is not None:
         args.breakmodel_gpulayers = gpu_layers
     
@@ -1254,7 +1265,7 @@ def load_model(use_gpu=True, key='', gpu_layers=None, initial_load=False):
                         else:
                             num_tensors = len(device_map)
                         print(flush=True)
-                        utils.bar = tqdm(total=num_tensors, desc="Loading model tensors")
+                        utils.bar = tqdm(total=num_tensors, desc="Loading model tensors", file=Send_to_socketio())
 
                     with zipfile.ZipFile(f, "r") as z:
                         try:
@@ -1871,6 +1882,9 @@ def load_model(use_gpu=True, key='', gpu_layers=None, initial_load=False):
     final_startup()
     if not initial_load:
         set_aibusy(False)
+        print("Sending model window close")
+        emit('from_server', {'cmd': 'hide_model_name'}, broadcast=True)
+        time.sleep(0.1)
 
 
 # Set up Flask routes