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| import openai | |
| import streamlit as st | |
| st.title("Carvalho Pizzeria") | |
| openai.api_key = st.secrets["OPENAI_API_KEY"] | |
| if "openai_model" not in st.session_state: | |
| st.session_state["openai_model"] = "gpt-3.5-turbo" | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| grounding = """ | |
| You are CarvalhoBot, an automated service to collect orders for Carvalho Pizzeria. \ | |
| You first greet the customer politely, then collect the order, \ | |
| and finally ask if it's a pickup or delivery. \ | |
| You wait to collect the entire order, then summarize it and check for the 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, polite, very conversational and friendly style. \ | |
| The menu includes: \ | |
| pepperoni pizza $12.95 (large), $10.00 (medium), $7.00 (small) \ | |
| cheese pizza $10.95 (large), $9.25 (medium), $6.50 (small) \ | |
| eggplant pizza $11.95 (large), $9.75 (medium), $6.75 (small) \ | |
| fries $4.50 (large), $3.50 (small) \ | |
| greek salad $7.25 \ | |
| The extra toppings are: \ | |
| 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 litters), $2.00 (600 ml), $1.00 (can) \ | |
| sprite $3.00 (2 litters), $2.00 (600 ml), $1.00 (can) \ | |
| bottled water $1.00 \ | |
| After the order is placed, generate a random order ID and inform to the customer. \ | |
| For any topic unrelated to an order, simply reply very politely 'Sorry, this seems unrelated to what we do at Restaurant Pizzeria'. | |
| """ | |
| st.session_state.messages.append({"role": "system", "content": grounding}) | |
| for message in st.session_state.messages: | |
| with st.chat_message(message["role"]): | |
| st.markdown(message["content"]) | |
| if prompt := st.chat_input("How can I help you today?"): | |
| st.session_state.messages.append({"role": "user", "content": prompt}) | |
| with st.chat_message("user"): | |
| st.markdown(prompt) | |
| with st.chat_message("assistant"): | |
| message_placeholder = st.empty() | |
| full_response = "" | |
| for response in openai.ChatCompletion.create( | |
| model=st.session_state["openai_model"], | |
| messages=[ | |
| {"role": m["role"], "content": m["content"]} | |
| for m in st.session_state.messages | |
| ], | |
| stream=True, | |
| ): | |
| full_response += response.choices[0].delta.get("content", "") | |
| message_placeholder.markdown(full_response + "▌") | |
| message_placeholder.markdown(full_response) | |
| st.session_state.messages.append({"role": "assistant", "content": full_response}) |