Update app.py

app.py

@@ -1,4 +1,5 @@
 import os
+import sys
 import time
 import random
 import yaml
@@ -21,6 +22,24 @@ N_ROWS = 20
 WAIT_TIME = 3600
 
 
+# Logger from https://github.com/gradio-app/gradio/issues/2362
+class Logger:
+    def __init__(self, filename):
+        self.terminal = sys.stdout
+        self.log = open(filename, "w")
+
+    def write(self, message):
+        self.terminal.write(message)
+        self.log.write(message)
+        
+    def flush(self):
+        self.terminal.flush()
+        self.log.flush()
+        
+    def isatty(self):
+        return False    
+
+
 def create_dataset() -> bool:
     """
     Use Scrape Open LLM Leaderboard to create a CSV dataset.
@@ -316,7 +335,7 @@ def merge_loop():
     # Evaluate model on Runpod
     create_pod(model_name, USERNAME)
 
-
+# Install scrape-open-llm-leaderboard and mergekit
 command = ["git", "clone", "-q", "https://github.com/Weyaxi/scrape-open-llm-leaderboard"]
 subprocess.run(command, check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
 
@@ -329,6 +348,8 @@ subprocess.run(command, check=True, stdout=subprocess.PIPE, stderr=subprocess.PI
 command = ["pip", "install", "-e", "mergekit"]
 subprocess.run(command, check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
 
+sys.stdout = Logger("output.log")
+
 # Gradio interface
 title = """
 <div align="center">
@@ -337,8 +358,10 @@ title = """
   <p><em>AutoMerger selects two 7B models on top of the Open LLM Leaderboard, combine them with a merge technique, and evaluate the resulting model.</em></p>
 </div>
 """
-with gr.Blocks() as demo:
+with gr.Blocks(theme=gr.themes.Glass()) as demo:
     gr.Markdown(title)
+    logs = gr.Textbox()
+    demo.load(read_logs, None, logs, every=1)
 demo.launch(server_name="0.0.0.0", prevent_thread_lock=True)
 
 print("Start AutoMerger...")