Update app.py

app.py

@@ -1,12 +1,11 @@
 import gradio as gr
-import json, os, vertexai, wandb
+import json, os, vertexai
 
 from dotenv import load_dotenv, find_dotenv
 _ = load_dotenv(find_dotenv())
 
 credentials = os.environ["CREDENTIALS"]
 project = os.environ["PROJECT"]
-wandb_api_key = os.environ["WANDB_API_KEY"]
 
 config = {
     "max_output_tokens": 800,
@@ -32,12 +31,6 @@ vertexai.init(project = project,
 from vertexai.preview.generative_models import GenerativeModel
 generation_model = GenerativeModel(config["model"])
 
-def wandb_log(prompt, completion):
-    wandb.login(key = wandb_api_key)
-    wandb.init(project = "vertex-ai-llm", config = config)
-    wandb.log({"prompt": str(prompt), "completion": str(completion)})
-    wandb.finish()
-
 def invoke(prompt):
     if (prompt == ""):
         raise gr.Error("Prompt is required.")
@@ -59,13 +52,10 @@ def invoke(prompt):
         completion = e
         
         raise gr.Error(e)
-    finally:
-        wandb_log(prompt, completion)
     
     return completion
 
-description = """<a href='https://www.gradio.app/'>Gradio</a> UI using the <a href='https://cloud.google.com/vertex-ai'>Google Vertex AI</a> API 
-                 with Gemini Pro model. Evaluation via <a href='https://wandb.ai/bstraehle'>Weights & Biases</a>."""
+description = "<a href='https://www.gradio.app/'>Gradio</a> UI using the <a href='https://cloud.google.com/vertex-ai'>Google Vertex AI</a> API with Gemini Pro model."
 
 gr.close_all()