Update app.py

app.py

@@ -7,55 +7,22 @@ import gradio as gr
 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
-
-# Set credentials to use the model
-my_credentials = {
-    "url": "https://us-south.ml.cloud.ibm.com",
-    "apikey": watsonx_API
-}
-
-# Generation parameters
-gen_parms = {
-    "max_new_tokens": 512,  # Adjust as needed for the length of the cover letter
-    "temperature": 0.7  # Adjust for creativity
+generate_params = {
+    GenParams.MAX_NEW_TOKENS: 250
 }
 
-# Initialize the model with credentials
-model = Model(model_id=model_id, credentials=my_credentials, gen_parms=gen_parms, project_id=project_id)
-
-# Function to generate customized career advice
-def generate_career_advice(field, position_name, current_qualifications, likes, skills):
-    # Craft the prompt for the model 
-    prompt = f"Generate a customized career advice using field: {field}, \
-    position_name: {position_name}, \
-    current_qualifications: {current_qualifications}, \
-    likes: {likes}, \
-    skills: {skills}."
-
-    generated_response = model.generate(prompt, gen_parms)
-
-    # Extract the generated text
-    career_advice = generated_response["results"][0]["generated_text"]
-    return career_advice
+model = Model(
+    model_id = 'meta-llama/llama-2-13b-chat', # you can also specify like: ModelTypes.LLAMA_2_70B_CHAT
+    params = generate_params,
+    credentials={
+        "apikey": watsonx_API,
+        "url": "https://us-south.ml.cloud.ibm.com"
+    },
+    project_id= project_id
+    )
 
-# 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.
-    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'"),
-        gr.Textbox(label="Current Qualifications (e.g., studying in high school, high school diploma, college diploma, etc.)", placeholder="Enter your current qualifications ..."),
-        gr.Textbox(label="Likes (e.g., I like working with my hands, I like to work outside, I like to help people, I like teaching, ...", placeholder="Enter activities you like ...", lines=10),
-        gr.Textbox(label="Skills (e.g., I am good at math, science, languages, computers, research, hand tools, etc.)", placeholder="Skills ...", lines=10),
-    ],
-    outputs=gr.Textbox(label="Customized Career Advice"),
-    title="Customized Career Advice",
-    description="Generate a customized career advice using field, position name, likes, and skills"
-)
+q = "How to be happy?"
+generated_response = model.generate(prompt=q)
+print(generated_response['results'][0]['generated_text'])
 
-# Launch the application
-career_advice_app.launch(server_name="0.0.0.0", debug=True, server_port=7860, share=True)