rtc_plugins/rtc_plugins.cpp

// rtc_plugins.cpp

#define IMPLEMENT_NUMPY_API  // 标记这是实现文件
#include "util/numpyStub.h"
#include "util/RTCContext.h"

// 提供转换接口
void** get_numpy_api() {
    return (void**)RTC_PLUGINS_ARRAY_API;
}


namespace py = boost::python;

int init(const char* selfUserId, const char* selfDisplayName, const char* selfRoomId, boost::python::object callback) {

    RTCContext::instance().setPyCallback(callback);
    bool res = RTCContext::instance().init(selfUserId, selfDisplayName, selfRoomId);
    if (res) {
        return 0;
    } else {
        return -1;
    }
}
int initRecv(const char* destRoomId, const char* srcUserId, const int16_t destChannelIndex) {

    bool res = RTCContext::instance().initRecv(destRoomId, srcUserId, destChannelIndex);
    if (res) {
        return 0;
    } else {
        return -1;
    }
}
int initSend(const char* srcRoomId, const char* destRoomId, const int16_t destChannelIndex, const uint8_t channelNum) {
    bool res = RTCContext::instance().initSend(srcRoomId, destRoomId, destChannelIndex, channelNum);
    if (res) {
        return 0;
    } else {
        return -1;
    }
}

py::object create_int16_array() {
    // 1. 定义数组维度（1维，长度为 4）
    npy_intp dims[1] = {4};

    // 2. 创建原生 C 数组（int16_t 数据）
    int16_t data[4] = {1, 2, -3, 4};  // 示例数据

    // 3. 通过 NumPy C API 创建 PyObject*
    PyObject* py_array = PyArray_SimpleNewFromData(
            1,              // 维度数
            dims,           // 各维度大小
            NPY_INT16,      // 数据类型（np.int16）
            data            // 数据指针
    );

    if (!py_array) {
        throw std::runtime_error("Failed to create NumPy array");
    }

    // 4. 转换为 py::object（自动管理引用计数）
    return py::object(py::handle<>(py_array));
}

int sendCustomAudioData(int16_t destChannelIndex, py::object pD,
                        int32_t sampleRate, uint64_t channelNum, uint64_t dataLen) {
    try {
        // 强制转换为 int16 连续数组
        PyObject* py_array = PyArray_FROM_OTF(
                pD.ptr(),
                NPY_INT16,
                NPY_ARRAY_IN_ARRAY | NPY_ARRAY_FORCECAST
        );
        if (!py_array) {
            throw std::runtime_error("Failed to convert input to int16 array");
        }

        // 修复点：使用花括号初始化
        py::object arr{py::handle<>(py_array)};

        // 检查数据长度
        PyArrayObject* npArray = reinterpret_cast<PyArrayObject*>(arr.ptr());
        if (PyArray_SIZE(npArray) != static_cast<npy_intp>(dataLen)) {
            Py_DECREF(py_array);
            throw std::runtime_error("Array length does not match dataLen");
        }

        // 处理数据...
        void* dataPtr = PyArray_DATA(npArray);
        int ret = RTCContext::instance().sendCustomAudioData(
                destChannelIndex, dataPtr, sampleRate, channelNum, dataLen
        );
        Py_DECREF(py_array);  // 释放临时数组
        return ret;
    } catch (...) {
        PyErr_SetString(PyExc_RuntimeError, "Invalid audio data");
        return -1;
    }
}

void init_numpy() {
    // 直接调用底层函数，绕过宏的问题
    if (_import_array() < 0) {
        PyErr_SetString(PyExc_ImportError, "numpy.core.multiarray failed to import");
        throw std::runtime_error("NumPy initialization failed");
    }
    std::cout << "NumPy API addr: " << PyArray_API << std::endl;
}
BOOST_PYTHON_MODULE(rtc_plugins) {
    try {
        init_numpy();
        void** numpyApi = (void**)PyArray_API;
        if (!numpyApi || !numpyApi[93]) { // 93是PyArray_SimpleNew的偏移量
            std::cout << "NumPy API corrupt! Key functions missing." << std::endl;
            PyErr_Print();
            throw std::runtime_error("Invalid NumPy API state");
        } else {
            RTCContext::instance().setNumpyApi(numpyApi);
            std::cout << "set numpyApi succ:" << numpyApi[93] << std::endl;
        }

        py::def("init", &init);
        py::def("initRecv", &initRecv);
        py::def("initSend", &initSend);
        py::def("sendCustomAudioData", &sendCustomAudioData);
    } catch (...) {
        PyErr_SetString(PyExc_RuntimeError, "Module initialization failed");
    }
}