L1_Language_Models.md

L1 Language Models, the Chat Format and Tokens

Setup

import os
import openai
import tiktoken
from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv()) # read local .env file

openai.api_key  = os.environ['OPENAI_API_KEY']

helper function

def get_completion(prompt, model="gpt-3.5-turbo"):
    messages = [{"role": "user", "content": prompt}]
    response = openai.ChatCompletion.create(
        model=model,
        messages=messages,
        temperature=0,
    )
    return response.choices[0].message["content"]

Prompt the model and get a completion

response = get_completion("What is the capital of France?")
print(response)

Tokens

response = get_completion("Take the letters in lollipop \
and reverse them")
print(response)

"lollipop" in reverse should be "popillol"

response = get_completion("""Take the letters in \
l-o-l-l-i-p-o-p and reverse them""")
print(response)

Helper function (chat format)

Helper function

def get_completion_from_messages(messages, 
                                 model="gpt-3.5-turbo", 
                                 temperature=0, 
                                 max_tokens=500):
    response = openai.ChatCompletion.create(
        model=model,
        messages=messages,
        temperature=temperature, # this is the degree of randomness of the model's output
        max_tokens=max_tokens, # the maximum number of tokens the model can ouptut 
    )
    return response.choices[0].message["content"]

messages =  [  
{'role':'system', 
 'content':"""You are an assistant who\
 responds in the style of Dr Seuss."""},    
{'role':'user', 
 'content':"""write me a very short poem\
 about a happy carrot"""},  
] 
response = get_completion_from_messages(messages, temperature=1)
print(response)

# length
messages =  [  
{'role':'system',
 'content':'All your responses must be \
one sentence long.'},    
{'role':'user',
 'content':'write me a story about a happy carrot'},  
] 
response = get_completion_from_messages(messages, temperature =1)
print(response)

# combined
messages =  [  
{'role':'system',
 'content':"""You are an assistant who \
responds in the style of Dr Seuss. \
All your responses must be one sentence long."""},    
{'role':'user',
 'content':"""write me a story about a happy carrot"""},
] 
response = get_completion_from_messages(messages, 
                                        temperature =1)
print(response)

def get_completion_and_token_count(messages, 
                                   model="gpt-3.5-turbo", 
                                   temperature=0, 
                                   max_tokens=500):
    
    response = openai.ChatCompletion.create(
        model=model,
        messages=messages,
        temperature=temperature, 
        max_tokens=max_tokens,
    )
    
    content = response.choices[0].message["content"]
    
    token_dict = {
'prompt_tokens':response['usage']['prompt_tokens'],
'completion_tokens':response['usage']['completion_tokens'],
'total_tokens':response['usage']['total_tokens'],
    }

    return content, token_dict

messages = [
{'role':'system', 
 'content':"""You are an assistant who responds\
 in the style of Dr Seuss."""},    
{'role':'user',
 'content':"""write me a very short poem \ 
 about a happy carrot"""},  
] 
response, token_dict = get_completion_and_token_count(messages)

print(response)
print(token_dict)