Assistant startup fix

setup.py

@@ -5,7 +5,7 @@
 
 setuptools.setup(
   name="text2text",
-  version="1.5.1",
+  version="1.5.2",
   author="artitw",
   author_email="[email protected]",
   description="Text2Text: Crosslingual NLP/G toolkit",

text2text/assistant.py

@@ -2,6 +2,7 @@
 import ollama
 import psutil
 import subprocess
+import time
 
 from llama_index.llms.ollama import Ollama
 from llama_index.core.llms import ChatMessage
@@ -19,19 +20,27 @@ def __init__(self, **kwargs):
     self.port = kwargs.get("port", 11434)
     self.model_url = f"{self.host}:{self.port}"
     self.model_name = kwargs.get("model_name", "llama3.1")
-    return_code = os.system("curl -fsSL https://ollama.com/install.sh | sh")
-    if return_code != 0:
-      print("Cannot install ollama.")
-    return_code = os.system("sudo systemctl enable ollama")
     self.load_model()
     self.client = ollama.Client(host=self.model_url)
 
+  def __del__(self):
+    ollama.delete(self.model_name)
+
   def load_model(self):
-    sub = subprocess.Popen(
-      f"ollama serve & ollama pull {self.model_name} & ollama run {self.model_name}", 
-      shell=True, 
-      stdout=subprocess.PIPE
-    )
+    return_code = os.system("sudo apt install -q -y lshw")
+    if return_code != 0:
+      print("Cannot install lshw.")
+    return_code = os.system("curl -fsSL https://ollama.com/install.sh | sh")
+    if return_code != 0:
+      print("Cannot install ollama.")
+    return_code = os.system("sudo systemctl enable ollama")
+    if return_code != 0:
+      print("Cannot enable ollama.")
+    sub = subprocess.Popen(["ollama", "serve"])
+    return_code = os.system("ollama -v")
+    if return_code != 0:
+      print("Cannot serve ollama.")
+    ollama.pull(self.model_name)
 
   def chat_completion(self, messages=[{"role": "user", "content": "hello"}], stream=False, schema=None, **kwargs):
     if is_port_in_use(self.port):

text2text/pytorch_pretrained_bert/modeling.py

@@ -160,8 +160,6 @@ def to_json_string(self):
 try:
     from apex.normalization.fused_layer_norm import FusedLayerNorm as BertLayerNorm
 except ImportError:
-    print("Better speed can be achieved with apex installed.")
-
     class BertLayerNorm(nn.Module):
         def __init__(self, hidden_size, eps=1e-5):
             """Construct a layernorm module in the TF style (epsilon inside the square root).