Question: I am currently trying to use OpenAI's most recent model: gpt-3.5-turbo. I am following a very basic tutorial. I am working from a Google Collab notebook. I have to make a request for each prompt in a list of prompts, which for sake of simplicity looks like this: prompts = ['What are your functionalities?', 'what is the best name for an ice-cream shop?', 'who won the premier league last year?']  I defined a function to do so: import openai # Load your API key from an environment variable or secret management service openai.api_key = 'my_API' def get_response(prompts: list, model = "gpt-3.5-turbo"): responses = [] restart_sequence = "\n" for item in prompts: response = openai.Completion.create( model=model, messages=[{"role": "user", "content": prompt}], temperature=0, max_tokens=20, top_p=1, frequency_penalty=0, presence_penalty=0 ) responses.append(response['choices'][0]['message']['content']) return responses  However, when I call responses = get_response(prompts=prompts[0:3]) I get the following error: InvalidRequestError: Unrecognized request argument supplied: messages  Any suggestions? Replacing the messages argument with prompt leads to the following error: InvalidRequestError: [{'role': 'user', 'content': 'What are your functionalities?'}] is valid under each of {'type': 'array', 'minItems': 1, 'items': {'oneOf': [{'type': 'integer'}, {'type': 'object', 'properties': {'buffer': {'type': 'string', 'description': 'A serialized numpy buffer'}, 'shape': {'type': 'array', 'items': {'type': 'integer'}, 'description': 'Array shape'}, 'dtype': {'type': 'string', 'description': 'Stringified dtype'}, 'token': {'type': 'string'}}}]}, 'example': '[1, 1313, 451, {"buffer": "abcdefgh", "shape": [1024], "dtype": "float16"}]'}, {'type': 'array', 'minItems': 1, 'maxItems': 2048, 'items': {'oneOf': [{'type': 'string'}, {'type': 'object', 'properties': {'buffer': {'type': 'string', 'description': 'A serialized numpy buffer'}, 'shape': {'type': 'array', 'items': {'type': 'integer'}, 'description': 'Array shape'}, 'dtype': {'type': 'string', 'description': 'Stringified dtype'}, 'token': {'type': 'string'}}}], 'default': '', 'example': 'This is a test.', 'nullable': False}} - 'prompt' 

Answer: Problem You used the wrong method to get a completion. When using the OpenAI SDK, whether you use Python or Node.js, you need to use the right method. Which method is the right one? It depends on the OpenAI model you want to use. Solution The tables below will help you figure out which method is the right one for a given OpenAI model. STEP 1: Find in the table below which API endpoint is compatible with the OpenAI model you want to use.    API endpoint Model group Model name     /v1/chat/completions • GPT-4  • GPT-3.5 • gpt-4 and dated model releases  • gpt-4-32k and dated model releases  • gpt-4-1106-preview  • gpt-4-vision-preview • gpt-3.5-turbo and dated model releases  • gpt-3.5-turbo-16k and dated model releases  • fine-tuned versions of gpt-3.5-turbo   /v1/completions (Legacy) • GPT-3.5  • GPT base • gpt-3.5-turbo-instruct  • babbage-002  • davinci-002   /v1/assistants  All models except gpt-3.5-turbo-0301 supported.  Retrieval tool requires gpt-4-1106-preview or gpt-3.5-turbo-1106.   /v1/audio/transcriptions Whisper • whisper-1   /v1/audio/translations Whisper • whisper-1   /v1/audio/speech TTS • tts-1  • tts-1-hd   /v1/fine_tuning/jobs • GPT-3.5  • GPT base • gpt-3.5-turbo  • babbage-002  • davinci-002   /v1/embeddings Embeddings • text-embedding-ada-002   /v1/moderations Moderations • text-moderation-stable  • text-moderation-latest     STEP 2: Find in the table below which method you need to use for the API endpoint you selected in the table above. Note: Pay attention, because you have to use the method that is compatible with your OpenAI SDK version.    API endpoint Method for the Python SDK v0.28.1 Method for the Python SDK >=v1.0.0 Method for the Node.js SDK v3.3.0 Method for the Node.js SDK >=v4.0.0     /v1/chat/completions openai.ChatCompletion.create openai.chat.completions.create openai.createChatCompletion openai.chat.completions.create   /v1/completions (Legacy) openai.Completion.create openai.completions.create openai.createCompletion openai.completions.create   /v1/assistants / openai.beta.assistants.create / openai.beta.assistants.create   /v1/audio/transcriptions openai.Audio.transcribe openai.audio.transcriptions.create openai.createTranscription openai.audio.transcriptions.create   /v1/audio/translations openai.Audio.translate openai.audio.translations.create openai.createTranslation openai.audio.translations.create   /v1/audio/speech / openai.audio.speech.create / openai.audio.speech.create   /v1/fine_tuning/jobs / openai.fine_tuning.jobs.create / openai.fineTuning.jobs.create   /v1/embeddings openai.Embedding.create openai.embeddings.create openai.createEmbedding openai.embeddings.create   /v1/moderations openai.Moderation.create openai.moderations.create openai.createModeration openai.moderations.create    Python SDK v1.0.0 working example for the gpt-3.5-turbo model If you run test.py, the OpenAI API will return the following completion:  Hello! How can I assist you today?  test.py import os from openai import OpenAI client = OpenAI( api_key = os.getenv("OPENAI_API_KEY"), ) completion = client.chat.completions.create( model = "gpt-3.5-turbo", messages = [ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "Hello!"}, ] ) print(completion.choices[0].message.content.strip())   Node.js SDK v4.0.0 working example for the gpt-3.5-turbo model If you run test.js, the OpenAI API will return the following completion:  Hello! How can I assist you today?  test.js const OpenAI = require("openai"); const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY, }); async function main() { const completion = await openai.chat.completions.create({ model: "gpt-3.5-turbo", messages: [ { role: "system", content: "You are a helpful assistant." }, { role: "user", content: "Hello!" }, ], }); console.log(completion.choices[0].message.content.trim()); } main();