update with edu-toolkit

handler.py

@@ -11,6 +11,7 @@ import transformers
 from transformers import BertTokenizer, BertForSequenceClassification
 import psutil
 from transformers.utils import logging
+from edu_toolkit import language_analysis
 
 transformers.logging.set_verbosity_debug()
 
@@ -249,7 +250,8 @@ class EndpointHandler():
         mem_info = psutil.virtual_memory()
         used_mem = mem_info.used / (1024 ** 3)  # Convert to gigabytes
         total_mem = mem_info.total / (1024 ** 3)  # Convert to gigabytes
-        logger.info(f"Used Memory before models loaded: {used_mem:.2f} GB, Total RAM: {total_mem:.2f} GB")
+        logger.info(
+            f"Used Memory before models loaded: {used_mem:.2f} GB, Total RAM: {total_mem:.2f} GB")
         # Uptake
         uptake_model = UptakeModel(
             self.device, self.tokenizer, self.input_builder)
@@ -259,7 +261,8 @@ class EndpointHandler():
         mem_info = psutil.virtual_memory()
         used_mem = mem_info.used / (1024 ** 3)  # Convert to gigabytes
         total_mem = mem_info.total / (1024 ** 3)  # Convert to gigabytes
-        logger.info(f"Used Memory after model 1 loaded: {used_mem:.2f} GB, Total Mem: {total_mem:.2f} GB")
+        logger.info(
+            f"Used Memory after model 1 loaded: {used_mem:.2f} GB, Total Mem: {total_mem:.2f} GB")
         logger.info(f"CPU Usage after model 1 loaded: {cpu_percent}%")
         # del uptake_model
         # cpu_percent = psutil.cpu_percent()
@@ -276,7 +279,8 @@ class EndpointHandler():
         mem_info = psutil.virtual_memory()
         used_mem = mem_info.used / (1024 ** 3)  # Convert to gigabytes
         total_mem = mem_info.total / (1024 ** 3)  # Convert to gigabytes
-        logger.info(f"Used Memory after model 2 loaded: {used_mem:.2f} GB, Total Mem: {total_mem:.2f} GB")
+        logger.info(
+            f"Used Memory after model 2 loaded: {used_mem:.2f} GB, Total Mem: {total_mem:.2f} GB")
         logger.info(f"CPU Usage after model 2 loaded: {cpu_percent}%")
         # print(f"CPU Usage after model 2 loaded: {cpu_percent}%")
         # del reasoning_model
@@ -296,7 +300,8 @@ class EndpointHandler():
         mem_info = psutil.virtual_memory()
         used_mem = mem_info.used / (1024 ** 3)  # Convert to gigabytes
         total_mem = mem_info.total / (1024 ** 3)  # Convert to gigabytes
-        logger.info(f"Used Memory after model 3 loaded: {used_mem:.2f} GB, Total Mem: {total_mem:.2f} GB")
+        logger.info(
+            f"Used Memory after model 3 loaded: {used_mem:.2f} GB, Total Mem: {total_mem:.2f} GB")
         # print(f"CPU Usage after model 3 loaded: {cpu_percent}%")
         # del question_model
         cpu_percent = psutil.cpu_percent()

requirements.txt

@@ -4,3 +4,4 @@ numpy==1.22.4
 scipy==1.7.3
 torch==1.10.2
 transformers==4.29.1
+edu-toolkit @ git+https://github.com/rosewang2008/edu-toolkit.git@main