Update app.py

app.py

@@ -1,8 +1,11 @@
 # Import necessary packages
+import os 
 from ibm_watson_machine_learning.foundation_models import Model
 import gradio as gr
 
-
+# Securely access the API key and project ID from environment variables
+watsonx_API = os.getenv("WATSONX_API") 
+project_id = os.getenv("PROJECT_ID")
 
 # Model and project settings
 model_id = "meta-llama/llama-2-13b-chat"  # Directly specifying the LLAMA2 model
@@ -18,13 +21,8 @@ gen_parms = {
     "temperature": 0.7  # Adjust for creativity
 }
 
-watsonx_API = os.getenv("watson_API") 
-project_id = os.getenv("project_id")
-space_id = None
-verify = False
-
 # Initialize the model
-model = Model(model_id, my_credentials, gen_parms, watson_API, project_id, space_id, verify)
+model = Model(model_id, watsonx_API, gen_parms, project_id)
 
 # Function to generate customized career advice
 def generate_career_advice(field, position_name, current_qualifications, likes, skills):
@@ -41,11 +39,10 @@ def generate_career_advice(field, position_name, current_qualifications, likes,
     career_advice = generated_response["results"][0]["generated_text"]
     return career_advice
 
-
-# Create Gradio interface for the cover letter generation application
+# Create Gradio interface for the career advice generation application
 career_advice_app = gr.Interface(
     fn=generate_career_advice,
-    allow_flagging="never", # Deactivate the flag function in gradio as it is not needed.
+    allow_flagging="never",  # Deactivate the flag function in gradio as it is not needed.
     inputs=[
         gr.Textbox(label="Field of Interest (e.g., healthcare, trades, social service, etc., or enter 'not sure')", placeholder="Enter the field which you are interested in... or type 'not sure'."),
         gr.Textbox(label="Position Name (e.g., nurse, personal support worker, software developer, plumber, etc., or enter 'not sure')", placeholder="Enter the name of the position you are interested in... or type 'not sure'"),
@@ -55,8 +52,9 @@ career_advice_app = gr.Interface(
     ],
     outputs=gr.Textbox(label="Customized Career Advice"),
     title="Customized Career Advice",
-    description="Generate a customized career advice using field, position name, likes and skills"
+    description="Generate a customized career advice using field, position name, likes, and skills"
 )
 
 # Launch the application
 career_advice_app.launch(server_name="0.0.0.0", debug=True, server_port=7860, share=True)
+