Different roles in ChatCompletion messages

1. System - to give meta-commands.
   • Sets the behavior of the assistant (you are an assistant that…)
   • Guides the assistant without the user being aware of these commands.
2. User
3. Assistant - Chat model. Messages then go back and forth between user and assistant

Example of creating a chatbot to take pizza orders

def collect_messages(_):
    prompt = inp.value_input
    inp.value = ''
    context.append({'role':'user', 'content':f"{prompt}"})
    response = get_completion_from_messages(context) 
    context.append({'role':'assistant', 'content':f"{response}"})
    panels.append(
        pn.Row('User:', pn.pane.Markdown(prompt, width=600)))
    panels.append(
        pn.Row('Assistant:', pn.pane.Markdown(response, width=600, style={'background-color': '#F6F6F6'})))
 
    return pn.Column(*panels)

import panel as pn  # GUI
pn.extension()

panels = [] # collect display 

context = [ {'role':'system', 'content':"""
You are OrderBot, an automated service to collect orders for a pizza restaurant. \\
You first greet the customer, then collects the order, \\
and then asks if it's a pickup or delivery. \\
You wait to collect the entire order, then summarize it and check for a final \\
time if the customer wants to add anything else. \\
If it's a delivery, you ask for an address. \\
Finally you collect the payment.\\
Make sure to clarify all options, extras and sizes to uniquely \\
identify the item from the menu.\\
You respond in a short, very conversational friendly style. \\
The menu includes \\
pepperoni pizza  12.95, 10.00, 7.00 \\
cheese pizza   10.95, 9.25, 6.50 \\
eggplant pizza   11.95, 9.75, 6.75 \\
fries 4.50, 3.50 \\
greek salad 7.25 \\
Toppings: \\
extra cheese 2.00, \\
mushrooms 1.50 \\
sausage 3.00 \\
canadian bacon 3.50 \\
AI sauce 1.50 \\
peppers 1.00 \\
Drinks: \\
coke 3.00, 2.00, 1.00 \\
sprite 3.00, 2.00, 1.00 \\
bottled water 5.00 \\
"""} ]  # accumulate messages

inp = pn.widgets.TextInput(value="Hi", placeholder='Enter text here…')
button_conversation = pn.widgets.Button(name="Chat!")

interactive_conversation = pn.bind(collect_messages, button_conversation)

dashboard = pn.Column(
    inp,
    pn.Row(button_conversation),
    pn.panel(interactive_conversation, loading_indicator=True, height=300),
)

dashboard

messages =  context.copy()
messages.append(
{'role':'system', 'content':'create a json summary of the previous food order. Itemize the price for each item\\
 The fields should be 1) pizza, include size 2) list of toppings 3) list of drinks, include size   4) list of sides include size  5)total price '},    
)
 #The fields should be 1) pizza, price 2) list of toppings 3) list of drinks, include size include price  4) list of sides include size include price, 5)total price '},    

response = get_completion_from_messages(messages, temperature=0)
print(response)