debug

app.py

@@ -1,61 +1,48 @@
 import subprocess
-import spaces
 import os
 import gradio as gr
 import json
 import base64
 from huggingface_hub import InferenceClient, login
 
-reinstall = "APP_REINSTALL"
-if os.getenv(reinstall):
-    node = "source /home/user/.bashrc && source /home/user/.nvm/nvm.sh && nvm install lts/iron && npm update -g npm"
-    subprocess.call(["pip","install","--upgrade","pip"])
+reinstall = os.getenv("APP_REINSTALL")
+if reinstall:
+    node_install_command = "source /home/user/.bashrc && source /home/user/.nvm/nvm.sh && nvm install --lts && npm update -g npm"
+    subprocess.call(["pip", "install", "--upgrade", "pip"])
     subprocess.call("curl -o- file:///home/user/app/data/setup.sh | bash", shell=True, executable='/bin/bash')
-    subprocess.Popen(node, shell=True, executable='/bin/bash').wait()
-    app_n8n = "npm install -g n8n"
-    subprocess.Popen(app_n8n, shell=True, executable='/bin/bash').wait()
-    service_env = "npm install -g forever"
-    subprocess.Popen(service_env, shell=True, executable='/bin/bash').wait()
+    subprocess.Popen(node_install_command, shell=True, executable='/bin/bash').wait()
+    subprocess.Popen("npm install -g n8n", shell=True, executable='/bin/bash').wait()
+    subprocess.Popen("npm install -g forever", shell=True, executable='/bin/bash').wait()
     subprocess.call("curl -o- file:///home/user/app/data/config_nginx.sh | bash", shell=True, executable='/bin/bash')
 
-subprocess.call(["forever","start","/home/user/.nvm/versions/node/v20.16.0/bin/n8n"])
-subprocess.call(["forever","start","/usr/sbin/nginx"], shell=True, executable='/bin/bash')
+subprocess.call(["forever", "start", "/home/user/.nvm/versions/node/v20.16.0/bin/n8n"])
+subprocess.call(["forever", "start", "/usr/sbin/nginx"], shell=True, executable='/bin/bash')
 
 # Get the API key from environment variables
-key = "UCODE_SECRET"
-login(os.getenv(key))
+api_key = os.getenv("UCODE_SECRET")
+login(api_key)
 
 # Initialize the InferenceClient with the specified model
 client = InferenceClient("meta-llama/Meta-Llama-3-70B-Instruct")
 
 def decode_base64_to_json(base64_str):
     try:
-        # Decode the base64 string
         decoded_bytes = base64.b64decode(base64_str)
-        # Convert bytes to string
         decoded_str = decoded_bytes.decode('utf-8')
-        # Fix escaped characters
         decoded_str = decoded_str.replace("\\'", "'").replace('\\"', '"').replace('\\\\', '\\')
         print(f"===================================================\nDecoded string: {decoded_str}\n===================================================")  # Log the decoded string
-        # Parse the JSON string
         return json.loads(decoded_str)
     except Exception as e:
         raise ValueError(f"Error decoding base64 to JSON: {str(e)}")
 
-
 @spaces.GPU(enable_queue=True)
 def chat_completion(user_input, max_tokens, temperature, top_p):
     try:
-        # Decode the base64-encoded JSON input
         input_data = decode_base64_to_json(user_input)
-        
-        # Ensure the input is a list of messages
         if not isinstance(input_data, list):
             raise ValueError("Input must be a list of messages.")
         
         response = ""
-        
-        # Generate chat completion
         for message in client.chat_completion(
             input_data,
             max_tokens=max_tokens,
@@ -70,13 +57,11 @@ def chat_completion(user_input, max_tokens, temperature, top_p):
     except Exception as e:
         return json.dumps({"status": "error", "message": str(e)})
 
-# Create Gradio components for user input
 user_input = gr.Textbox(label="User Input as Base64-encoded JSON String", lines=10)
 max_tokens = gr.Slider(minimum=1, maximum=8092, value=150, label="Max Tokens")
 temperature = gr.Slider(minimum=0.0, maximum=1.0, value=0.7, label="Temperature")
 top_p = gr.Slider(minimum=0.0, maximum=1.0, value=0.9, label="Top P")
 
-# Set up Gradio interface
 iface = gr.Interface(
     fn=chat_completion,
     inputs=[user_input, max_tokens, temperature, top_p],
@@ -85,5 +70,4 @@ iface = gr.Interface(
     description="Provide Base64-encoded JSON input with a list of messages and set the max tokens, temperature, and top_p to generate a chat completion."
 )
 
-# Launch the Gradio interface
-iface.launch(share=False,server_name="0.0.0.0",server_port=7000)
+iface.launch(share=False, server_name="0.0.0.0", server_port=7000)