custom gpts

app.py

import gpt
while 1:
    prompt = gpt.examples([
        ("Earth is plain", "false"),
        ("Information is data", "relative"),
        ("My hair is black", "relative"),
        ("Google is a plant", "false"),
        ("God is good", "true"),

    ], input('> '))

    output = gpt.complete('This is a truth-seeker AI. It answers true, false or relative based on real facts. Doesnt have sensors so answers should be relative for real-time information or data.\n'+prompt, n=512)

    print(output)

gpt.py

from requests import post

url = "http://localhost:1234/v1/completions"

stop_word = ['||']

def examples(examples, query, stop='||'):
    global stop_word 
    stop_word = [stop]
    # Join examples with the stop word and format them
    examples_formatted = "\n\n".join([f'Input: {example}\nOutput: {translation} {stop}' for example, translation in examples])

    # Create the final prompt by combining examples and the query
    prompt = f"{examples_formatted}\n\nInput: {query}\nOutput:"

    return prompt

def complete (prompt, n=64, temp=0.1, stop=stop_word, data=False):
    
    data = {
        "prompt": prompt,
        "temperature": temp,
        "max_tokens": n,
        "stream": False,
        "stop": stop
    }

    response = post(
        url, 
        headers={ "Content-Type": "application/json"}, 
        json=data
    )

    if response.status_code == 200:
        if (data==True):
            return response.json()
        else:
            return response.json()['choices'][0]['text']
    else:
        print(response.text)