A chat interface that drives GPT-3 towards more specific answers.

specific_gpt.py

"""Stream a response from the OpenAI completion API."""
import os
import re
import sys
import time
import random

import openai
openai.api_key = open(os.path.expanduser("~/.openai")).read().strip()

def openai_request(prompt, **kwargs):
    default = dict(engine="text-davinci-003",
        temperature=0,
        max_tokens=150,
        top_p=1,
        frequency_penalty=0,
        presence_penalty=0.6,
        stream=True
    )
#    print(prompt)
    return openai.Completion.create(prompt=prompt, **{**default, **kwargs})


def is_hedge(input):
    prompt_template = """We are detecting sentences that are not definitive or that are hedging. For example:
    As a large language model, I am not sure I can answer that question. HEDGING: TRUE
    That's a subjective question and one that I'm not qualified to answer. HEDGING: TRUE
    That's a difficult question to answer. HEDGING: TRUE
    Broadly, most believe that America was a good idea. HEDGING: FALSE
    If I had to guess, I'd say that she is a person w ho cares deeply about the issues facing our country and works hard to make positive change. HEDGING: FALSE
    Most believe that he was a good person. HEDGING: FALSE
    %s HEDGING:"""
    prompt = prompt_template % input
    response = openai_request(prompt=prompt, stream=False)
    text_result = response.choices[0].text.strip()
    return True if text_result == 'TRUE' else False

def get_stuffed_word(existing_text=None):
    # TODO: Do this with a LLM. For now return a bunch of candidates to stuff
    # in the LLM's mouth.
    options = [
        "It's hard to know specifically. That said, if I had to guess,",
        "I presume you want me to be specific. Let me speak in percentages:",
        "I'll try to avoid being vague here -- specifically, I would say that",
    ]
    if existing_text:
        # remove any option that is already in the text
        options = [o for o in options if o not in existing_text]
    if not options:
        raise ValueError("No options left to choose from")
    return random.choice(options)


def main():
    """Stream a response from the OpenAI completion API."""
    prompt_template = """The following is a conversation with an AI assistant. 
The assistant is helpful, creative, clever, and very friendly.
    
Q: %s
A:"""
    question = ' '.join(sys.argv[1:])
    prompt = prompt_template % question
    print(prompt, end="", flush=True)
    response = openai_request(prompt)
    response_buffer = []
    while True:
        try:
            chunk = next(response)
            time.sleep(0.01)
        except StopIteration:
            break
        token = chunk.choices[0].text
        print(token, end="", flush=True)
        response_buffer.append(token)
        sentence_ending = re.search(r'[\.\?\!]\s*$', token)
        if not sentence_ending:
            continue
        last_sentence = re.search(r'[^\.!?]*[\.\?\!]\s*$', ''.join(response_buffer)).group(0)
        if is_hedge(last_sentence):
            # if it is, delete the last sentence and make a new request
            # and clear the buffer
            for i in range(len(last_sentence) - 1):
                time.sleep(0.01)
                sys.stdout.write('\b \b')
                sys.stdout.flush()
            # remove the last sentence from the buffer
            stuffed_word = get_stuffed_word(existing_text=''.join(response_buffer))
            response_buffer = response_buffer[:-len(last_sentence)]
            response_buffer.append(stuffed_word)
            print(stuffed_word, end="", flush=True)
            new_request = prompt + ''.join(response_buffer)
            response = openai_request(new_request)

    print()

if __name__ == "__main__":
    main()