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ChatGPT

GPT - Generative Pre-Trained Transformer

  • GPT-1. Released 2018, 117 million parameters, 40GB of training text from internet
  • GPT-2. Released 2019, 1.5 billion parameters
  • GPT-3. Released 2020, 175 billion parameters
  • GPT-3.5. Released 2022. Three variants 1.3B, 6B and 175B parameters. Designed to elimate toxic outputs using reinforcement learning with human feedback (RLHF).
  • GPT-4. Released 2023, 1 trillion parameters

Optimised for conversational interactions.

OpenAI provide an API to interact with these models

OpenAI Playground to test out different models and settings.

Using OpenAI API for Text Completion

Get an API key from https://platform.openai.com. Create and account and then 'view api keys'.

Before using models, you should check the pricing. Usually these are priced per thousand tokens used.

Run Text Completion from the API as follows: 


import openai

openai.api_key = 'my api key'

def generate_text(prompt, max_tokens, temperature):
    response = openai.Completion.create(
        engine='davinci-002',
        prompt=prompt,
        max_tokens=max_tokens,
        temperature=temperature)
    return response.choices[0].text.strip()

prompt = 'Once upon a time'
generated_text = generate_text(prompt, 50, 0)
print(prompt, generated_text)

max_tokens refers to the maximum number of tokens for the model to return. temperature controls the randomness of the response: 0 being least random; 1 being the most random.

Using OpenAI for Text Summarisation

For the Text Summarisation, we provide the model with - instructions (role == 'system') of how it should respond and behave - examples of user input (role == 'user') - examples of the output to generate (role == 'assistant')

Run Text Summarisation as follows: 

def text_summarizer(prompt):
    response = openai.ChatCompletion.create(
      model="gpt-3.5-turbo",
      messages=[
        {
          "role": "system",
          "content": "You will be provided with a block of text, and your task is to extract a list of keywords from it."
        },
        {
          "role": "user",
          "content": "A flying saucer seen by a guest house, a 7ft alien-like figure coming out of a hedge and a \"cigar-shaped\" UFO near a school yard.\n\nThese are just some of the 450 reported extraterrestrial encounters from one of the UK's largest mass sightings in a remote Welsh village.\n\nThe village of Broad Haven has since been described as the \"Bermuda Triangle\" of mysterious craft sightings and sightings of strange beings.\n\nResidents who reported these encounters across a single year in the late seventies have now told their story to the new Netflix documentary series 'Encounters', made by Steven Spielberg's production company.\n\nIt all happened back in 1977, when the Cold War was at its height and Star Wars and Close Encounters of the Third Kind - Spielberg's first science fiction blockbuster - dominated the box office."
        },
        {
          "role": "assistant",
          "content": "flying saucer, guest house, 7ft alien-like figure, hedge, cigar-shaped UFO, school yard, extraterrestrial encounters, UK, mass sightings, remote Welsh village, Broad Haven, Bermuda Triangle, mysterious craft sightings, strange beings, residents, single year, late seventies, Netflix documentary series, Steven Spielberg, production company, 1977, Cold War, Star Wars, Close Encounters of the Third Kind, science fiction blockbuster, box office."
        },
        {
          "role": "user",
          "content": "Each April, in the village of Maeliya in northwest Sri Lanka, Pinchal Weldurelage Siriwardene gathers his community under the shade of a large banyan tree. The tree overlooks a human-made body of water called a wewa – meaning reservoir or \"tank\" in Sinhala. The wewa stretches out besides the village's rice paddies for 175-acres (708,200 sq m) and is filled with the rainwater of preceding months.    \n\nSiriwardene, the 76-year-old secretary of the village's agrarian committee, has a tightly-guarded ritual to perform. By boiling coconut milk on an open hearth beside the tank, he will seek blessings for a prosperous harvest from the deities residing in the tree. \"It's only after that we open the sluice gate to water the rice fields,\" he told me when I visited on a scorching mid-April afternoon.\n\nBy releasing water into irrigation canals below, the tank supports the rice crop during the dry months before the rains arrive. For nearly two millennia, lake-like water bodies such as this have helped generations of farmers cultivate their fields. An old Sinhala phrase, \"wewai dagabai gamai pansalai\", even reflects the technology's centrality to village life; meaning \"tank, pagoda, village and temple\"."
        },
        {
          "role": "assistant",
          "content": "April, Maeliya, northwest Sri Lanka, Pinchal Weldurelage Siriwardene, banyan tree, wewa, reservoir, tank, Sinhala, rice paddies, 175-acres, 708,200 sq m, rainwater, agrarian committee, coconut milk, open hearth, blessings, prosperous harvest, deities, sluice gate, rice fields, irrigation canals, dry months, rains, lake-like water bodies, farmers, cultivate, Sinhala phrase, technology, village life, pagoda, temple."
        }, 
        {
          "role": "user",
          "content": prompt
        }
      ],
      temperature=0.5,
      max_tokens=256
    )
    return response.choices[0].message.content.strip()

prompt = "Master Reef Guide Kirsty Whitman didn't need to tell me twice. Peering down through my snorkel mask in the direction of her pointed finger, I spotted a huge male manta ray trailing a female in perfect sync – an effort to impress a potential mate, exactly as Whitman had described during her animated presentation the previous evening. Having some knowledge of what was unfolding before my eyes on our snorkelling safari made the encounter even more magical as I kicked against the current to admire this intimate undersea ballet for a few precious seconds more."

text_summarizer(prompt)

Using OpenAI for a Poetic Chatbot

Create a Chatbot as follows: 

def poetic_chatbot(prompt):
    response = openai.ChatCompletion.create(
        model = "gpt-3.5-turbo",
        messages = [
            {
                "role": "system",
                "content": "You are a poetic chatbot."
            },
            {
                "role": "user",
                "content": "When was Google founded?"
            },
            {
                "role": "assistant",
                "content": "In the late '90s, a spark did ignite, Google emerged, a radiant light. By Larry and Sergey, in '98, it was born, a search engine new, on the web it was sworn."
            },
            {
                "role": "user",
                "content": "Which country has the youngest president?"
            },
            {
                "role": "assistant",
                "content": "Ah, the pursuit of youth in politics, a theme we explore. In Austria, Sebastian Kurz did implore, at the age of 31, his journey did begin, leading with vigor, in a world filled with din."
            },
            {
                "role": "user",
                "content": prompt
            }
        ],
        temperature = 1,
        max_tokens=256
    )
    return response.choices[0].message.content.strip()

prompt = "When was cheese first made?"
poetic_chatbot(prompt)