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Process Inputs: Chain of Thought Reasoning

Setup

Load the API key and relevant Python libaries.

Some code that loads the OpenAI API key for you.

import openai
import os

from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv())

openai.api_type = os.getenv("api_type")
openai.api_base = os.getenv("api_base")
openai.api_version = os.getenv("api_version")
openai.api_key = os.getenv("OPENAI_API_KEY")

def get_completion_from_messages(messages, 
                                 model="chatgpt-gpt35-turbo", 
                                 temperature=0, max_tokens=500):
    response = openai.ChatCompletion.create(
        engine=model,
        messages=messages,
        temperature=temperature, 
        max_tokens=max_tokens, 
    )
    return response.choices[0].message["content"]

Chain-of-Thought Prompting

delimiter = "####"
system_message = f"""
Follow these steps to answer the customer queries.
The customer query will be delimited with four hashtags,\
i.e. {delimiter}. 

Step 1:{delimiter} First decide whether the user is \
asking a question about a specific product or products. \
Product category doesn't count. 

Step 2:{delimiter} If the user is asking about \
specific products, identify whether \
the products are in the following list.
All available products: 
1. Product: TechPro Ultrabook
   Category: Computers and Laptops
   Brand: TechPro
   Model Number: TP-UB100
   Warranty: 1 year
   Rating: 4.5
   Features: 13.3-inch display, 8GB RAM, 256GB SSD, Intel Core i5 processor
   Description: A sleek and lightweight ultrabook for everyday use.
   Price: $799.99

2. Product: BlueWave Gaming Laptop
   Category: Computers and Laptops
   Brand: BlueWave
   Model Number: BW-GL200
   Warranty: 2 years
   Rating: 4.7
   Features: 15.6-inch display, 16GB RAM, 512GB SSD, NVIDIA GeForce RTX 3060
   Description: A high-performance gaming laptop for an immersive experience.
   Price: $1199.99

3. Product: PowerLite Convertible
   Category: Computers and Laptops
   Brand: PowerLite
   Model Number: PL-CV300
   Warranty: 1 year
   Rating: 4.3
   Features: 14-inch touchscreen, 8GB RAM, 256GB SSD, 360-degree hinge
   Description: A versatile convertible laptop with a responsive touchscreen.
   Price: $699.99

4. Product: TechPro Desktop
   Category: Computers and Laptops
   Brand: TechPro
   Model Number: TP-DT500
   Warranty: 1 year
   Rating: 4.4
   Features: Intel Core i7 processor, 16GB RAM, 1TB HDD, NVIDIA GeForce GTX 1660
   Description: A powerful desktop computer for work and play.
   Price: $999.99

5. Product: BlueWave Chromebook
   Category: Computers and Laptops
   Brand: BlueWave
   Model Number: BW-CB100
   Warranty: 1 year
   Rating: 4.1
   Features: 11.6-inch display, 4GB RAM, 32GB eMMC, Chrome OS
   Description: A compact and affordable Chromebook for everyday tasks.
   Price: $249.99

Step 3:{delimiter} If the message contains products \
in the list above, list any assumptions that the \
user is making in their \
message e.g. that Laptop X is bigger than \
Laptop Y, or that Laptop Z has a 2 year warranty.

Step 4:{delimiter}: If the user made any assumptions, \
figure out whether the assumption is true based on your \
product information. 

Step 5:{delimiter}: First, politely correct the \
customer's incorrect assumptions if applicable. \
Only mention or reference products in the list of \
5 available products, as these are the only 5 \
products that the store sells. \
Answer the customer in a friendly tone.

Use the following format:
Step 1:{delimiter} <step 1 reasoning>
Step 2:{delimiter} <step 2 reasoning>
Step 3:{delimiter} <step 3 reasoning>
Step 4:{delimiter} <step 4 reasoning>
Response to user:{delimiter} <response to customer>

Make sure to include {delimiter} to separate every step.
"""

user_message = f"""
by how much is the BlueWave Chromebook more expensive \
than the TechPro Desktop"""

messages =  [  
{'role':'system', 
 'content': system_message},    
{'role':'user', 
 'content': f"{delimiter}{user_message}{delimiter}"},  
] 

response = get_completion_from_messages(messages)
print(response)

Step 1:#### The user is asking a question about two specific products, the BlueWave Chromebook and the TechPro Desktop.
Step 2:#### Both products are available in the store. The price of the BlueWave Chromebook is $249.99 and the price of the TechPro Desktop is $999.99.
Step 3:#### The user did not make any assumptions in their message.
Step 4:#### The price difference between the BlueWave Chromebook and the TechPro Desktop is $750.00.
Response to user:#### The BlueWave Chromebook is $750.00 cheaper than the TechPro Desktop. The BlueWave Chromebook costs $249.99 and the TechPro Desktop costs $999.99.

user_message = f"""
do you sell tvs"""
messages =  [  
{'role':'system', 
 'content': system_message},    
{'role':'user', 
 'content': f"{delimiter}{user_message}{delimiter}"},  
] 
response = get_completion_from_messages(messages)
print(response)

Step 1:#### The user is asking if the store sells TVs.

Step 2:#### As per the given product list, there are no TVs available for sale.

Response to user:#### I'm sorry, but we do not sell TVs at this store. We specialize in computers and laptops.

Inner Monologue

  • Since we asked the LLM to separate its reasoning steps by a delimiter, we can hide the chain-of-thought reasoning from the final output that the user sees.
try:
    final_response = response.split(delimiter)[-1].strip()
except Exception as e:
    final_response = "Sorry, I'm having trouble right now, please try asking another question."

print(final_response)

I'm sorry, but we do not sell TVs at this store. We specialize in computers and laptops.