import re, requests, os

env = os.environ

OPENAI_PUBLIC_KEY = env['OPENAI_PUBLIC_KEY']

​

public_end_point = 'https://api.openai.com/v1/completions'

headers = {'authorization': f"Bearer {OPENAI_PUBLIC_KEY}"}

​

#This function provides the context. Note that that it will consume a lot of tokens (input tokens)

def get_last_5_summary_chats(chats):

    res =''

    for index, question_response in enumerate(chats[-5:]):

        res+= f"prompt{index}: {question_response[0]} response{index}: {question_response[1]} "

    if(len(chats)> 3):

        res = "Give short responses only. "+ res

    return res

​

#Store your chat history in session_chats

session_chats = []

​

#Set Input Parameters to the endpoint

data = { "model": 'text-davinci-003', "max_tokens": 400, "temperature": 1, "top_p": 0.6}

​

for ind in range(10):

    prev_context = get_last_5_summary_chats(session_chats)

    prompt = input("Ask your question:\t").strip()

    data['prompt'] = f"{prev_context} {prompt}".strip()

    r = requests.post(public_end_point, headers=headers, json=data)

    public_response = r.json()

    response_text = public_response['choices'][0]['text'].strip()

    print(f"QUESTION:\t{prompt}\n")

    print(f"RESPONSE:\t {response_text}\n\n")

    session_chats.append([prompt, response_text])