OpenAI ChatGPT (GPT-3.5) API error: "InvalidRequestError: Unrecognized request argument supplied: messages"
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'
Answers:
Problem
You used the wrong function to get a completion. When using the OpenAI library (Python or NodeJS), you need to use the right function. Which is the right one? It depends on the model you want to use.
Solution
The tables below will help you figure out which function is the right one for a given OpenAI model.
First, find in the table below which API endpoint is compatible with the model you want to use.
API endpoint
Model group
Model name
/v1/chat/completions
GPT-3.5 and GPT-4
gpt-4, gpt-4-0613, gpt-4-32k, gpt-4-32k-0613, gpt-3.5-turbo, gpt-3.5-turbo-0613, gpt-3.5-turbo-16k, gpt-3.5-turbo-16k-0613
/v1/completions
GPT-3
text-davinci-003, text-davinci-002, text-curie-001, text-babbage-001, text-ada-001
/v1/edits
Edits
text-davinci-edit-001, code-davinci-edit-001
/v1/audio/transcriptions
Whisper
whisper-1
/v1/audio/translations
Whisper
whisper-1
/v1/fine-tunes
GPT-3
davinci, curie, babbage, ada
/v1/embeddings
Embeddings
text-embedding-ada-002, text-search-ada-doc-001
/v1/moderations
Moderation
text-moderation-stable, text-moderation-latest
Second, find in the table below which function you need to use.
API endpoint
Python function
NodeJS function
/v1/chat/completions
openai.ChatCompletion.create
openai.createChatCompletion
/v1/completions
openai.Completion.create
openai.createCompletion
/v1/edits
openai.Edit.create
openai.createEdit
/v1/audio/transcriptions
openai.Audio.transcribe
openai.createTranscription
/v1/audio/translations
openai.Audio.translate
openai.createTranslation
/v1/fine-tunes
openai.FineTune.create
openai.createFineTune
/v1/embeddings
openai.Embedding.create
openai.createEmbedding
/v1/moderations
openai.Moderation.create
openai.createModeration
Python working example for the gpt-3.5-turbo (i.e., Chat Completions API)
If you run test.py the OpenAI API will return the following completion:
Hello there! How can I assist you today?
test.py
import openai
import os
openai.api_key = os.getenv('OPENAI_API_KEY')
completion = openai.ChatCompletion.create(
model = 'gpt-3.5-turbo',
messages = [
{'role': 'user', 'content': 'Hello!'}
],
temperature = 0
)
print(completion['choices'][0]['message']['content'])
NodeJS working example for the gpt-3.5-turbo (i.e., Chat Completions API)
If you run test.js the OpenAI API will return the following completion:
Hello there! How can I assist you today?
test.js
const { Configuration, OpenAIApi } = require('openai');
const configuration = new Configuration({
apiKey: process.env.OPENAI_API_KEY,
});
const openai = new OpenAIApi(configuration);
async function getCompletionFromOpenAI() {
const completion = await openai.createChatCompletion({
model: 'gpt-3.5-turbo',
messages: [
{ role: 'user', content: 'Hello!' }
],
temperature: 0,
});
console.log(completion.data.choices[0].message.content);
}
getCompletionFromOpenAI();
response = openai.ChatCompletion.create(
model='gpt-3.5-turbo',
messages=[
{"role": "user", "content": "What is openAI?"}],
max_tokens=193,
temperature=0,
)
print(response)
print(response["choices"][0]["message"]["content"])
You should define messages=[{"role": "user", "content": prompt}] outside of your response variable and call that in response variable like:
messages=[{"role": "user", "content": prompt}]
for item in prompts:
response = openai.Completion.create(
model=model,
messages=messages,
temperature=0,
max_tokens=20,
top_p=1,
frequency_penalty=0,
presence_penalty=0
)
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'
Problem
You used the wrong function to get a completion. When using the OpenAI library (Python or NodeJS), you need to use the right function. Which is the right one? It depends on the model you want to use.
Solution
The tables below will help you figure out which function is the right one for a given OpenAI model.
First, find in the table below which API endpoint is compatible with the model you want to use.
| API endpoint | Model group | Model name |
|---|---|---|
| /v1/chat/completions | GPT-3.5 and GPT-4 | gpt-4, gpt-4-0613, gpt-4-32k, gpt-4-32k-0613, gpt-3.5-turbo, gpt-3.5-turbo-0613, gpt-3.5-turbo-16k, gpt-3.5-turbo-16k-0613 |
| /v1/completions | GPT-3 | text-davinci-003, text-davinci-002, text-curie-001, text-babbage-001, text-ada-001 |
| /v1/edits | Edits | text-davinci-edit-001, code-davinci-edit-001 |
| /v1/audio/transcriptions | Whisper | whisper-1 |
| /v1/audio/translations | Whisper | whisper-1 |
| /v1/fine-tunes | GPT-3 | davinci, curie, babbage, ada |
| /v1/embeddings | Embeddings | text-embedding-ada-002, text-search-ada-doc-001 |
| /v1/moderations | Moderation | text-moderation-stable, text-moderation-latest |
Second, find in the table below which function you need to use.
| API endpoint | Python function | NodeJS function |
|---|---|---|
| /v1/chat/completions | openai.ChatCompletion.create | openai.createChatCompletion |
| /v1/completions | openai.Completion.create | openai.createCompletion |
| /v1/edits | openai.Edit.create | openai.createEdit |
| /v1/audio/transcriptions | openai.Audio.transcribe | openai.createTranscription |
| /v1/audio/translations | openai.Audio.translate | openai.createTranslation |
| /v1/fine-tunes | openai.FineTune.create | openai.createFineTune |
| /v1/embeddings | openai.Embedding.create | openai.createEmbedding |
| /v1/moderations | openai.Moderation.create | openai.createModeration |
Python working example for the gpt-3.5-turbo (i.e., Chat Completions API)
If you run test.py the OpenAI API will return the following completion:
Hello there! How can I assist you today?
test.py
import openai
import os
openai.api_key = os.getenv('OPENAI_API_KEY')
completion = openai.ChatCompletion.create(
model = 'gpt-3.5-turbo',
messages = [
{'role': 'user', 'content': 'Hello!'}
],
temperature = 0
)
print(completion['choices'][0]['message']['content'])
NodeJS working example for the gpt-3.5-turbo (i.e., Chat Completions API)
If you run test.js the OpenAI API will return the following completion:
Hello there! How can I assist you today?
test.js
const { Configuration, OpenAIApi } = require('openai');
const configuration = new Configuration({
apiKey: process.env.OPENAI_API_KEY,
});
const openai = new OpenAIApi(configuration);
async function getCompletionFromOpenAI() {
const completion = await openai.createChatCompletion({
model: 'gpt-3.5-turbo',
messages: [
{ role: 'user', content: 'Hello!' }
],
temperature: 0,
});
console.log(completion.data.choices[0].message.content);
}
getCompletionFromOpenAI();
response = openai.ChatCompletion.create(
model='gpt-3.5-turbo',
messages=[
{"role": "user", "content": "What is openAI?"}],
max_tokens=193,
temperature=0,
)
print(response)
print(response["choices"][0]["message"]["content"])
You should define messages=[{"role": "user", "content": prompt}] outside of your response variable and call that in response variable like:
messages=[{"role": "user", "content": prompt}]
for item in prompts:
response = openai.Completion.create(
model=model,
messages=messages,
temperature=0,
max_tokens=20,
top_p=1,
frequency_penalty=0,
presence_penalty=0
)