Connecting to ChatGPT using API
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I tried connecting to Chat GPT with the following web instructions and get the error as reflected ...
prompt = 'What is the capital of France?';
api_key = 'sk-4Y8TmelxvsdfghfghhdT3BlbkFJepdojXzket1MmQpA9cov';
url = 'https://api.openai.com/v1/engines/davinci/completions';
options = weboptions('KeyName','Authorization','KeyValue',['Bearer ' api_key],'MediaType','application/json');
data = webwrite(url,'prompt',prompt,'max_tokens',2048,'model','text-davinci-003','stop','',options);
answer = loadjson(data);
answer = answer.choices{1}.text;
disp(answer)
Does anyone know how to connect MATLAB to Chat GPT to send prompts and retrieve back the responses. Also how to send data over to fine tune the model and then to further prompt that model?
It would be good for Mathworks to double quick release a toolbox on FileExchange for this as Python already has an OpenAI library. Seems like Mathworks is always one step behind Python these days.
Thx
4 件のコメント
the cyclist
2023 年 1 月 15 日
If that's your actual API key, I'd remove it
John Adams
2023 年 1 月 15 日
Wii Che
2023 年 2 月 19 日
% Extract the response text
response_text = response.Body.Data;
response_text = response_text.choices(1).text;
disp(response_text);
There is an error, is it a version problem
Yakoub
2023 年 10 月 28 日

採用された回答
その他の回答 (3 件)
Duncan Carlsmith
2023 年 2 月 23 日
3 投票
See Generate MATLAB code using ChatGPT API at https://www.mathworks.com/matlabcentral/fileexchange/125220-generate-matlab-code-using-chatgpt-api for a Live Script that implements the great answers here. Thank you all so much!
You get different code for the same prompt each time. For the prompt used, there is often a minor bug. Great for teaching debugging skills. ;) I'll let you find the bugs in the example I provided.
2 件のコメント
Hans Scharler
2023 年 2 月 23 日
Your project works perfectly. Thanks for sharing!
Duncan Carlsmith
2023 年 2 月 24 日
Thanks for checking it out!
% Define the prompt
prompt = "What is the capital of France?";
% Define the API endpoint
api_endpoint = 'https://api.openai.com/v1/chat/completions';
% Define the API key from https://platform.openai.com/account/api-keys
api_key = "sk-XXXYYYZZZ";
% Define the headers
headers = ["Content-Type", "application/json"; "Authorization", "Bearer " + api_key];
% Define the data
message = containers.Map({'role', 'content'}, {'user', prompt});
data = containers.Map({'model', 'messages'}, {'gpt-3.5-turbo', {message}});
% Convert the data to JSON
data = jsonencode(data);
% Send the POST request
options = weboptions('RequestMethod', 'post', 'HeaderFields', headers);
response = webwrite(api_endpoint, data, options);
% Return the response
response = response.choices.message.content;
disp(prompt)
disp(response)
1 件のコメント
thijs buuron
2023 年 1 月 20 日
1 投票
If you have the curl command (get it from the network part of the console of you webbrowser). You could use: https://curlconverter.com/matlab/ wich converts it to matlab code for you.
2 件のコメント
Gregorio Ariel Guerrero Moral
2023 年 4 月 6 日
編集済み: Gregorio Ariel Guerrero Moral
2023 年 4 月 6 日
works very well the two options
%% Option1: https://curlconverter.com/matlab/
uri = 'https://api.openai.com/v1/chat/completions';
body = struct(...
'model', 'gpt-3.5-turbo',...
'messages', {{
struct(...
'role', 'user',...
'content', 'What is the capital of France?'...
)
}}...
);
options = weboptions(...
'MediaType', 'application/json',...
'HeaderFields', {'Authorization' ['Bearer ' getenv('OPENAI_API_KEY')]}...
);
response = webwrite(uri, body, options);
disp(response.choices.message.content)
And the second options
%% Option 2: HTTP Interface https://curlconverter.com/matlab/
import matlab.net.*
import matlab.net.http.*
import matlab.net.http.io.*
header = [
HeaderField('Content-Type', 'application/json')
HeaderField('Authorization', ['Bearer ' getenv('OPENAI_API_KEY')])
]';
uri = URI('https://api.openai.com/v1/chat/completions');
body = JSONProvider(struct(...
'model', 'gpt-3.5-turbo',...
'messages', {{
struct(...
'role', 'user',...
'content', 'What is the capital of France?'...
)
}}...
));
response = RequestMessage('post', header, body).send(uri.EncodedURI);
disp(response.choices.message.content)
Remember to setup in you OS the variable OPENAI_API_KEY.
The result of this chat is:

tony
2023 年 9 月 10 日
thank you
not working for a longer quesion
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