OpenAI-C++ library is a community-maintained library which provides convenient access to the OpenAI API from applications written in the C++ language.
The library is small with two header files (only one if you already use Nlohmann Json).
No special requirement. You should already have these :
- C++11/C++14/C++17/C++20 compatible compiler
- libcurl (check Install curl to make sure you have the development package)
The library should implement all requests on OpenAI references. If any are missing (due to an update), feel free to open an issue.
The library consists of two files: include/openai/openai.hpp and include/openai/nlohmann/json.hpp.
Just copy the include/openaicpp folder in your project and you can use #include "openai.hpp" in your code. That is all.
Note: OpenAI-CPP uses Nlohmann Json which is available in
include/json.hpp. Feel free to use your own copy for faster compile time build.
The library needs to be configured with your account's secret key which is available on the website. It is recommended to set your OPENAI_API_KEY environment variable before using the library (or you can also set the API key directly in the code):
export OPENAI_API_KEY='sk-...'The following code is available at examples/00-showcase.cpp.
#include "openai.hpp"
#include <iostream>
int main() {
openai::start(); // Will use the api key provided by `OPENAI_API_KEY` environment variable
// openai::start("your_API_key", "optional_organization"); // Or you can handle it yourself
auto completion = openai::completion().create(R"({
"model": "text-davinci-003",
"prompt": "Say this is a test",
"max_tokens": 7,
"temperature": 0
})"_json); // Using user-defined (raw) string literals
std::cout << "Response is:\n" << completion.dump(2) << '\n';
auto image = openai::image().create({
{ "prompt", "A cute koala playing the violin"},
{ "n", 1 },
{ "size", "512x512" }
}); // Using initializer lists
std::cout << "Image URL is: " << image["data"][0]["url"] << '\n';
}The output received looks like:
>> request: https://api.openai.com/v1/completions {"max_tokens":7,"model":"text-davinci-003","prompt":"Say this is a test","temperature":0}
Response is:
{
"choices": [
{
"finish_reason": "length",
"index": 0,
"logprobs": null,
"text": "\n\nThis is indeed a test"
}
],
"created": 1674121840,
"id": "cmpl-6aLr6jPhtxpLyu9rNsJFKDHU3SHpe",
"model": "text-davinci-003",
"object": "text_completion",
"usage": {
"completion_tokens": 7,
"prompt_tokens": 5,
"total_tokens": 12
}
}
>> request: https://api.openai.com/v1/images/generations {"n":1,"prompt":"A cute koala playing the violin","size":"512x512"}
Image URL is: "https://oaidalleapiprodscus.blob.core.windows.net/private/org-WaIMDdGHNwJiXAmjegDHE6AM/user-bCrYDjR21ly46316ZbdgqvKf/img-sysAePXF2c8yu28AIoZLLmEG.png?st=2023-01-19T20%3A35%3A19Z&se=2023-01-19T22%3A35%3A19Z&sp=r&sv=2021-08-06&sr=b&rscd=inline&rsct=image/png&skoid=6aaadede-4fb3-4698-a8f6-684d7786b067&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2023-01-19T18%3A10%3A41Z&ske=2023-01-20T18%3A10%3A41Z&sks=b&skv=2021-08-06&sig=nWkcGTTCsWigHHocYP%2BsyiV5FJL6izpAe3OVvX1GLuI%3D"
Since Openai::Json is a typedef to a nlohmann::json, you get all the features provided by the latter one (conversions, STL like access, ...).
mkdir build && cd build
cmake .. && make
examples/[whatever]In your project, if you want to get verbose output like when running the examples, you can define #define OPENAI_VERBOSE_OUTPUT.
By default, OpenAI-CPP will throw a runtime error exception if the curl request does not succeed. You are free to handle these exceptions the way you like.
You can prevent throw exceptions by setting setThrowException(false) (see example in examples/09-instances.cpp). If you do that, a warning will be displayed instead.
You can use the openai::post() or openai::get() methods to fully control what you are sending (e.g. can be useful when a new method from OpenAI API is available and not provided by OpenAI-CPP yet).
Here are two approaches to keep alive the OpenAI-CPP session in your program so you can use it anytime, anywhere.
This is the default behavior. OpenAI-CPP provides free convenient functions : openai::start(const std::string& token) and openai::instance().
Initialize and configure the OpenAI-CPP instance with:
auto& openai = openai::start();When you are in another scope and you have lost the openai reference, you can grab it again with :
auto& openai = openai::instance();It might not be the recommended way but since we generally want to handle only one OpenAI instance (one token), this approach is highly convenient.
An other approach is to pass the OpenAI instance by reference, store it, and call the appropriate methods when needed.
void bar(openai::OpenAI& openai) {
openai.completion.create({
{"model", "text-davinci-003"},
{"prompt", "Say bar() function called"}
});
}
int main() {
openai::OpenAI openai_instance{"your_api_key"};
bar(openai_instance);
}You can use a std::reference_wrapper as shown in examples/09-instances.cpp.
This strategy is useful if you have to manage several OpenAI-CPP instances with different secret keys.
Note: If you are using WSL then you are not concerned by the following.
According to Install Curl on Windows,
Windows 10 comes with the curl tool bundled with the operating system since version 1804
However, you still might have difficulties handling libcurl where CMake throws Could NOT find CURL (missing: CURL_LIBRARY CURL_INCLUDE_DIR).
You can try to follow one the 2 ways proposed by the the Curl Install Curl on Windows.
Another way to solve this is to grab the curl version for Windows here, copy the content of include
in appropriate folders available visible in your PATH (e.g. if in your Git installation [...]/Git/mingw64/include/).
You also need to grab the curl.lib and the libcurl.dll files from here and copy them in appropriate folders (e.g. if in your Git installation [...]/Git/mingw64/lib/).
mkdir build && cd build
cmake .. -DCMAKE_GENERATOR_PLATFORM=x64
cmake --build .
cmake --build . --target 00-showcase # For a specific targetOr if you prefer using GNU GCC on Windows
cmake -G "MSYS Makefiles" -D CMAKE_CXX_COMPILER=g++ ..
makeThis work has been mainly inspired by slacking and the curl wrapper code from cpr.
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