formats it as part of the messages list as user role content.

• formats it as part of the messages list as user role content.

• Outputs responses that are printed to the console and formatted and added to the messages list as assistant role content.

This means that every time a new question is asked, a running transcript of the conversation so far is sent along with the latest question. Since the model has no memory, you need to send an updated transcript with each new question or the model will lose context of the previous questions and answers.

PythonCopy

import os
import openai
openai.api_type = "azure"
openai.api_version = "2023-05-15" 
openai.api_base = os.getenv("OPENAI_API_BASE")  # Your Azure OpenAI resource's endpoint value .
openai.api_key = os.getenv("OPENAI_API_KEY")

conversation=[{"role": "system", "content": "You are a helpful assistant."}]

while True:
    user_input = input()      
    conversation.append({"role": "user", "content": user_input})

    response = openai.ChatCompletion.create(
        engine="gpt-3.5-turbo", # The deployment name you chose when you deployed the GPT-35-turbo or GPT-4 model.
        messages=conversation
    )

    conversation.append({"role": "assistant", "content": response["choices"][0]["message"]["content"]})
    print("\n" + response['choices'][0]['message']['content'] + "\n")

When you run the code above you will get a blank console window. Enter your first question in the window and then hit enter. Once the response is returned, you can repeat the process and keep asking questions.