Add Python API (#31)

+[flake8]
+show-source=true
+statistics=true
+max-line-length = 80
+
+exclude =
+  .git,
+  ./cmake,

+#!/usr/bin/env bash
+
+set -e
+
+log() {
+  # This function is from espnet
+  local fname=${BASH_SOURCE[1]##*/}
+  echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
+}
+
+
+repo_url=https://huggingface.co/csukuangfj/sherpa-onnx-lstm-en-2023-02-17
+
+log "Start testing ${repo_url}"
+repo=$(basename $repo_url)
+log "Download pretrained model and test-data from $repo_url"
+
+GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
+pushd $repo
+git lfs pull --include "*.onnx"
+popd
+
+python3 -c "import sherpa_onnx; print(sherpa_onnx.__file__)"
+sherpa_onnx_version=$(python3 -c "import sherpa_onnx; print(sherpa_onnx.__version__)")
+
+echo "sherpa_onnx version: $sherpa_onnx_version"
+
+pwd
+ls -lh
+
+ls -lh $repo
+
+python3 python-api-examples/decode-file.py

@@ -47,7 +47,7 @@ jobs:
           cd build
           cmake -D CMAKE_BUILD_TYPE=Release ..
 
-      - name: Build sherpa for macos
+      - name: Build sherpa-onnx for macos
         shell: bash
         run: |
           cd build

+name: run-python-test
+
+on:
+  push:
+    branches:
+      - master
+    paths:
+      - '.github/workflows/run-python-test.yaml'
+      - '.github/scripts/test-python.sh'
+      - 'CMakeLists.txt'
+      - 'cmake/**'
+      - 'sherpa-onnx/csrc/*'
+  pull_request:
+    branches:
+      - master
+    paths:
+      - '.github/workflows/run-python-test.yaml'
+      - '.github/scripts/test-python.sh'
+      - 'CMakeLists.txt'
+      - 'cmake/**'
+      - 'sherpa-onnx/csrc/*'
+
+concurrency:
+  group: run-python-test-${{ github.ref }}
+  cancel-in-progress: true
+
+permissions:
+  contents: read
+
+jobs:
+  run-python-test:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-latest, macos-latest, windows-latest]
+        python-version: ["3.7", "3.8", "3.9", "3.10"]
+
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          fetch-depth: 0
+
+      - name: Setup Python
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install Python dependencies
+        shell: bash
+        run: |
+          python3 -m pip install --upgrade pip numpy
+
+      - name: Install sherpa-onnx
+        shell: bash
+        run: |
+          python3 setup.py install
+
+      - name: Test sherpa-onnx
+        shell: bash
+        run: |
+          .github/scripts/test-python.sh

@@ -5,3 +5,6 @@ onnxruntime-*
 icefall-*
 run.sh
 sherpa-onnx-*
+__pycache__
+dist/
+sherpa_onnx.egg-info/

 cmake_minimum_required(VERSION 3.13 FATAL_ERROR)
 project(sherpa-onnx)
 
-set(SHERPA_ONNX_VERSION "1.0")
+set(SHERPA_ONNX_VERSION "1.1")
+
+# Disable warning about
+#
+# "The DOWNLOAD_EXTRACT_TIMESTAMP option was not given and policy CMP0135 is
+#  not set.
+if (CMAKE_VERSION VERSION_GREATER_EQUAL "3.24.0")
+  cmake_policy(SET CMP0135 NEW)
+endif()
+
+option(SHERPA_ONNX_ENABLE_PYTHON "Whether to build Python" OFF)
+option(SHERPA_ONNX_ENABLE_TESTS "Whether to build tests" OFF)
+option(BUILD_SHARED_LIBS "Whether to build shared libraries" OFF)
 
 set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/lib")
 set(CMAKE_LIBRARY_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/lib")
@@ -20,13 +32,20 @@ endif()
 set(CMAKE_INSTALL_RPATH ${SHERPA_ONNX_RPATH_ORIGIN})
 set(CMAKE_BUILD_RPATH ${SHERPA_ONNX_RPATH_ORIGIN})
 
-set(BUILD_SHARED_LIBS ON)
+if(WIN32 AND BUILD_SHARED_LIBS)
+  message(STATUS "Set BUILD_SHARED_LIBS to OFF for windows")
+  set(BUILD_SHARED_LIBS OFF)
+endif()
 
 if(NOT CMAKE_BUILD_TYPE)
   message(STATUS "No CMAKE_BUILD_TYPE given, default to Release")
   set(CMAKE_BUILD_TYPE Release)
 endif()
+
 message(STATUS "CMAKE_BUILD_TYPE: ${CMAKE_BUILD_TYPE}")
+message(STATUS "CMAKE_INSTALL_PREFIX: ${CMAKE_INSTALL_PREFIX}")
+message(STATUS "BUILD_SHARED_LIBS ${BUILD_SHARED_LIBS}")
+message(STATUS "SHERPA_ONNX_ENABLE_PYTHON ${SHERPA_ONNX_ENABLE_PYTHON}")
 
 set(CMAKE_CXX_STANDARD 14 CACHE STRING "The C++ version to be used.")
 set(CMAKE_CXX_EXTENSIONS OFF)
@@ -37,4 +56,12 @@ list(APPEND CMAKE_MODULE_PATH ${CMAKE_SOURCE_DIR}/cmake)
 include(kaldi-native-fbank)
 include(onnxruntime)
 
+if(SHERPA_ONNX_ENABLE_PYTHON)
+  include(pybind11)
+endif()
+
+if(SHERPA_ONNX_ENABLE_TESTS)
+  enable_testing()
+endif()
+
 add_subdirectory(sherpa-onnx)

+# cmake/cmake_extension.py
+# Copyright (c)  2023  Xiaomi Corporation
+#
+# flake8: noqa
+
+import os
+import platform
+import sys
+from pathlib import Path
+
+import setuptools
+from setuptools.command.build_ext import build_ext
+
+
+def is_for_pypi():
+    ans = os.environ.get("SHERPA_ONNX_IS_FOR_PYPI", None)
+    return ans is not None
+
+
+def is_macos():
+    return platform.system() == "Darwin"
+
+
+def is_windows():
+    return platform.system() == "Windows"
+
+
+try:
+    from wheel.bdist_wheel import bdist_wheel as _bdist_wheel
+
+    class bdist_wheel(_bdist_wheel):
+        def finalize_options(self):
+            _bdist_wheel.finalize_options(self)
+            # In this case, the generated wheel has a name in the form
+            # sherpa-xxx-pyxx-none-any.whl
+            if is_for_pypi() and not is_macos():
+                self.root_is_pure = True
+            else:
+                # The generated wheel has a name ending with
+                # -linux_x86_64.whl
+                self.root_is_pure = False
+
+except ImportError:
+    bdist_wheel = None
+
+
+def cmake_extension(name, *args, **kwargs) -> setuptools.Extension:
+    kwargs["language"] = "c++"
+    sources = []
+    return setuptools.Extension(name, sources, *args, **kwargs)
+
+
+class BuildExtension(build_ext):
+    def build_extension(self, ext: setuptools.extension.Extension):
+        # build/temp.linux-x86_64-3.8
+        os.makedirs(self.build_temp, exist_ok=True)
+
+        # build/lib.linux-x86_64-3.8
+        os.makedirs(self.build_lib, exist_ok=True)
+
+        install_dir = Path(self.build_lib).resolve() / "sherpa_onnx"
+
+        sherpa_onnx_dir = Path(__file__).parent.parent.resolve()
+
+        cmake_args = os.environ.get("SHERPA_ONNX_CMAKE_ARGS", "")
+        make_args = os.environ.get("SHERPA_ONNX_MAKE_ARGS", "")
+        system_make_args = os.environ.get("MAKEFLAGS", "")
+
+        if cmake_args == "":
+            cmake_args = "-DCMAKE_BUILD_TYPE=Release"
+
+        extra_cmake_args = f" -DCMAKE_INSTALL_PREFIX={install_dir} "
+        if not is_windows():
+            extra_cmake_args += " -DBUILD_SHARED_LIBS=ON "
+        else:
+            extra_cmake_args += " -DBUILD_SHARED_LIBS=OFF "
+        extra_cmake_args += " -DSHERPA_ONNX_ENABLE_PYTHON=ON "
+
+        if "PYTHON_EXECUTABLE" not in cmake_args:
+            print(f"Setting PYTHON_EXECUTABLE to {sys.executable}")
+            cmake_args += f" -DPYTHON_EXECUTABLE={sys.executable}"
+
+        cmake_args += extra_cmake_args
+
+        if is_windows():
+            build_cmd = f"""
+         cmake {cmake_args} -B {self.build_temp} -S {sherpa_onnx_dir}
+         cmake --build {self.build_temp} --target install --config Release -- -m
+            """
+            print(f"build command is:\n{build_cmd}")
+            ret = os.system(
+                f"cmake {cmake_args} -B {self.build_temp} -S {sherpa_onnx_dir}"
+            )
+            if ret != 0:
+                raise Exception("Failed to configure sherpa")
+
+            ret = os.system(
+                f"cmake --build {self.build_temp} --target install --config Release -- -m"  # noqa
+            )
+            if ret != 0:
+                raise Exception("Failed to build and install sherpa")
+        else:
+            if make_args == "" and system_make_args == "":
+                print("for fast compilation, run:")
+                print('export SHERPA_ONNX_MAKE_ARGS="-j"; python setup.py install')
+                print('Setting make_args to "-j4"')
+                make_args = "-j4"
+
+            build_cmd = f"""
+                cd {self.build_temp}
+
+                cmake {cmake_args} {sherpa_onnx_dir}
+
+                make {make_args} install/strip
+            """
+            print(f"build command is:\n{build_cmd}")
+
+            ret = os.system(build_cmd)
+            if ret != 0:
+                raise Exception(
+                    "\nBuild sherpa-onnx failed. Please check the error message.\n"
+                    "You can ask for help by creating an issue on GitHub.\n"
+                    "\nClick:\n\thttps://github.com/k2-fsa/sherpa-onnx/issues/new\n"  # noqa
+                )

 function(download_kaldi_native_fbank)
   include(FetchContent)
 
-  set(kaldi_native_fbank_URL  "https://github.com/csukuangfj/kaldi-native-fbank/archive/refs/tags/v1.12.tar.gz")
-  set(kaldi_native_fbank_HASH "SHA256=8f4dfc3f6ddb1adcd9ac0ae87743ebc6cbcae147aacf9d46e76fa54134e12b44")
+  set(kaldi_native_fbank_URL  "https://github.com/csukuangfj/kaldi-native-fbank/archive/refs/tags/v1.13.tar.gz")
+  set(kaldi_native_fbank_HASH "SHA256=1f4d228f9fe3e3e9f92a74a7eecd2489071a03982e4ba6d7c70fc5fa7444df57")
 
   set(KALDI_NATIVE_FBANK_BUILD_TESTS OFF CACHE BOOL "" FORCE)
   set(KALDI_NATIVE_FBANK_BUILD_PYTHON OFF CACHE BOOL "" FORCE)
@@ -11,11 +11,11 @@ function(download_kaldi_native_fbank)
   # If you don't have access to the Internet,
   # please pre-download kaldi-native-fbank
   set(possible_file_locations
-    $ENV{HOME}/Downloads/kaldi-native-fbank-1.12.tar.gz
-    ${PROJECT_SOURCE_DIR}/kaldi-native-fbank-1.12.tar.gz
-    ${PROJECT_BINARY_DIR}/kaldi-native-fbank-1.12.tar.gz
-    /tmp/kaldi-native-fbank-1.12.tar.gz
-    /star-fj/fangjun/download/github/kaldi-native-fbank-1.12.tar.gz
+    $ENV{HOME}/Downloads/kaldi-native-fbank-1.13.tar.gz
+    ${PROJECT_SOURCE_DIR}/kaldi-native-fbank-1.13.tar.gz
+    ${PROJECT_BINARY_DIR}/kaldi-native-fbank-1.13.tar.gz
+    /tmp/kaldi-native-fbank-1.13.tar.gz
+    /star-fj/fangjun/download/github/kaldi-native-fbank-1.13.tar.gz
   )
 
   foreach(f IN LISTS possible_file_locations)
@@ -44,6 +44,7 @@ function(download_kaldi_native_fbank)
     INTERFACE
       ${kaldi_native_fbank_SOURCE_DIR}/
   )
+  install(TARGETS kaldi-native-fbank-core DESTINATION lib)
 endfunction()
 
 download_kaldi_native_fbank()

@@ -85,6 +85,7 @@ function(download_onnxruntime)
   message(STATUS "location_onnxruntime: ${location_onnxruntime}")
 
   add_library(onnxruntime SHARED IMPORTED)
+
   set_target_properties(onnxruntime PROPERTIES
     IMPORTED_LOCATION ${location_onnxruntime}
     INTERFACE_INCLUDE_DIRECTORIES "${onnxruntime_SOURCE_DIR}/include"
@@ -100,6 +101,18 @@ function(download_onnxruntime)
         ${CMAKE_BINARY_DIR}/bin/${CMAKE_BUILD_TYPE}
     )
   endif()
+
+
+  if(UNIX AND NOT APPLE)
+    file(GLOB onnxruntime_lib_files "${onnxruntime_SOURCE_DIR}/lib/lib*")
+  elseif(APPLE)
+    file(GLOB onnxruntime_lib_files "${onnxruntime_SOURCE_DIR}/lib/lib*dylib")
+  elseif(WIN32)
+    file(GLOB onnxruntime_lib_files "${onnxruntime_SOURCE_DIR}/lib/*.dll")
+  endif()
+
+  message(STATUS "onnxruntime lib files: ${onnxruntime_lib_files}")
+  install(FILES ${onnxruntime_lib_files} DESTINATION lib)
 endfunction()
 
 download_onnxruntime()

+function(download_pybind11)
+  include(FetchContent)
+
+  set(pybind11_URL  "https://github.com/pybind/pybind11/archive/refs/tags/v2.10.2.tar.gz")
+  set(pybind11_HASH "SHA256=93bd1e625e43e03028a3ea7389bba5d3f9f2596abc074b068e70f4ef9b1314ae")
+
+  # If you don't have access to the Internet,
+  # please pre-download pybind11
+  set(possible_file_locations
+    $ENV{HOME}/Downloads/pybind11-2.10.2.tar.gz
+    ${PROJECT_SOURCE_DIR}/pybind11-2.10.2.tar.gz
+    ${PROJECT_BINARY_DIR}/pybind11-2.10.2.tar.gz
+    /tmp/pybind11-2.10.2.tar.gz
+    /star-fj/fangjun/download/github/pybind11-2.10.2.tar.gz
+  )
+
+  foreach(f IN LISTS possible_file_locations)
+    if(EXISTS ${f})
+      set(pybind11_URL  "file://${f}")
+      break()
+    endif()
+  endforeach()
+
+  FetchContent_Declare(pybind11
+    URL               ${pybind11_URL}
+    URL_HASH          ${pybind11_HASH}
+  )
+
+  FetchContent_GetProperties(pybind11)
+  if(NOT pybind11_POPULATED)
+    message(STATUS "Downloading pybind11 from ${pybind11_URL}")
+    FetchContent_Populate(pybind11)
+  endif()
+  message(STATUS "pybind11 is downloaded to ${pybind11_SOURCE_DIR}")
+  add_subdirectory(${pybind11_SOURCE_DIR} ${pybind11_BINARY_DIR} EXCLUDE_FROM_ALL)
+endfunction()
+
+download_pybind11()

+#!/usr/bin/env python3
+
+"""
+This file demonstrates how to use sherpa-onnx Python API to recognize
+a single file.
+
+Please refer to
+https://k2-fsa.github.io/sherpa/onnx/index.html
+to install sherpa-onnx and to download the pre-trained models
+used in this file.
+"""
+import wave
+import time
+
+import numpy as np
+import sherpa_onnx
+
+
+def main():
+    sample_rate = 16000
+    num_threads = 4
+    recognizer = sherpa_onnx.OnlineRecognizer(
+        tokens="./sherpa-onnx-lstm-en-2023-02-17/tokens.txt",
+        encoder="./sherpa-onnx-lstm-en-2023-02-17/encoder-epoch-99-avg-1.onnx",
+        decoder="./sherpa-onnx-lstm-en-2023-02-17/decoder-epoch-99-avg-1.onnx",
+        joiner="./sherpa-onnx-lstm-en-2023-02-17/joiner-epoch-99-avg-1.onnx",
+        num_threads=num_threads,
+        sample_rate=sample_rate,
+        feature_dim=80,
+    )
+    filename = "./sherpa-onnx-lstm-en-2023-02-17/test_wavs/1089-134686-0001.wav"
+    with wave.open(filename) as f:
+        assert f.getframerate() == sample_rate, f.getframerate()
+        assert f.getnchannels() == 1, f.getnchannels()
+        assert f.getsampwidth() == 2, f.getsampwidth()  # it is in bytes
+        num_samples = f.getnframes()
+        samples = f.readframes(num_samples)
+        samples_int16 = np.frombuffer(samples, dtype=np.int16)
+        samples_float32 = samples_int16.astype(np.float32)
+
+        samples_float32 = samples_float32 / 32768
+
+    duration = len(samples_float32) / sample_rate
+
+    start_time = time.time()
+    print("Started!")
+
+    stream = recognizer.create_stream()
+
+    stream.accept_waveform(sample_rate, samples_float32)
+
+    tail_paddings = np.zeros(int(0.2 * sample_rate), dtype=np.float32)
+    stream.accept_waveform(sample_rate, tail_paddings)
+
+    stream.input_finished()
+
+    while recognizer.is_ready(stream):
+        recognizer.decode_stream(stream)
+
+    print(recognizer.get_result(stream))
+
+    print("Done!")
+    end_time = time.time()
+    elapsed_seconds = end_time - start_time
+    rtf = elapsed_seconds / duration
+    print(f"num_threads: {num_threads}")
+    print(f"Wave duration: {duration:.3f} s")
+    print(f"Elapsed time: {elapsed_seconds:.3f} s")
+    print(f"Real time factor (RTF): {elapsed_seconds:.3f}/{duration:.3f} = {rtf:.3f}")
+
+
+if __name__ == "__main__":
+    main()

+#!/usr/bin/env python3
+
+import os
+import re
+import sys
+from pathlib import Path
+
+import setuptools
+
+from cmake.cmake_extension import (
+    BuildExtension,
+    bdist_wheel,
+    cmake_extension,
+    is_windows,
+)
+
+
+def read_long_description():
+    with open("README.md", encoding="utf8") as f:
+        readme = f.read()
+    return readme
+
+
+def get_package_version():
+    with open("CMakeLists.txt") as f:
+        content = f.read()
+
+    match = re.search(r"set\(SHERPA_ONNX_VERSION (.*)\)", content)
+    latest_version = match.group(1).strip('"')
+    return latest_version
+
+
+package_name = "sherpa-onnx"
+
+with open("sherpa-onnx/python/sherpa_onnx/__init__.py", "a") as f:
+    f.write(f"__version__ = '{get_package_version()}'\n")
+
+install_requires = [
+    "numpy",
+]
+
+setuptools.setup(
+    name=package_name,
+    python_requires=">=3.6",
+    install_requires=install_requires,
+    version=get_package_version(),
+    author="The sherpa-onnx development team",
+    author_email="dpovey@gmail.com",
+    package_dir={
+        "sherpa_onnx": "sherpa-onnx/python/sherpa_onnx",
+    },
+    packages=["sherpa_onnx"],
+    url="https://github.com/k2-fsa/sherpa-onnx",
+    long_description=read_long_description(),
+    long_description_content_type="text/markdown",
+    ext_modules=[cmake_extension("_sherpa_onnx")],
+    cmdclass={"build_ext": BuildExtension, "bdist_wheel": bdist_wheel},
+    zip_safe=False,
+    classifiers=[
+        "Programming Language :: C++",
+        "Programming Language :: Python",
+        "Topic :: Scientific/Engineering :: Artificial Intelligence",
+    ],
+    license="Apache licensed, as found in the LICENSE file",
+)
+
+with open("sherpa-onnx/python/sherpa_onnx/__init__.py", "r") as f:
+    lines = f.readlines()
+
+with open("sherpa-onnx/python/sherpa_onnx/__init__.py", "w") as f:
+    for line in lines:
+        if "__version__" in line:
+            # skip __version__ = "x.x.x"
+            continue
+        f.write(line)

 add_subdirectory(csrc)
+if(SHERPA_ONNX_ENABLE_PYTHON)
+  add_subdirectory(python)
+endif()

 include_directories(${CMAKE_SOURCE_DIR})
 
-add_executable(sherpa-onnx
+add_library(sherpa-onnx-core
   features.cc
   online-lstm-transducer-model.cc
   online-recognizer.cc
@@ -9,15 +9,21 @@ add_executable(sherpa-onnx
   online-transducer-model-config.cc
   online-transducer-model.cc
   onnx-utils.cc
-  sherpa-onnx.cc
   symbol-table.cc
   wave-reader.cc
 )
 
-target_link_libraries(sherpa-onnx
+target_link_libraries(sherpa-onnx-core
   onnxruntime
   kaldi-native-fbank-core
 )
 
-add_executable(sherpa-onnx-show-info show-onnx-info.cc)
-target_link_libraries(sherpa-onnx-show-info onnxruntime)
+add_executable(sherpa-onnx sherpa-onnx.cc)
+
+target_link_libraries(sherpa-onnx sherpa-onnx-core)
+if(NOT WIN32)
+  target_link_libraries(sherpa-onnx "-Wl,-rpath,${SHERPA_ONNX_RPATH_ORIGIN}/../lib")
+endif()
+
+install(TARGETS sherpa-onnx-core DESTINATION lib)
+install(TARGETS sherpa-onnx DESTINATION bin)

-// sherpa/csrc/features.cc
+// sherpa-onnx/csrc/features.cc
 //
 // Copyright (c)  2023  Xiaomi Corporation
 

-// sherpa/csrc/features.h
+// sherpa-onnx/csrc/features.h
 //
 // Copyright (c)  2023  Xiaomi Corporation
 

-// sherpa/csrc/online-lstm-transducer-model.cc
+// sherpa-onnx/csrc/online-lstm-transducer-model.cc
 //
 // Copyright (c)  2023  Xiaomi Corporation
 #include "sherpa-onnx/csrc/online-lstm-transducer-model.h"
@@ -232,7 +232,7 @@ std::vector<Ort::Value> OnlineLstmTransducerModel::GetEncoderInitStates() {
 
 std::pair<Ort::Value, std::vector<Ort::Value>>
 OnlineLstmTransducerModel::RunEncoder(Ort::Value features,
-                                      std::vector<Ort::Value> &states) {
+                                      std::vector<Ort::Value> states) {
   auto memory_info =
       Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
 

-// sherpa/csrc/online-lstm-transducer-model.h
+// sherpa-onnx/csrc/online-lstm-transducer-model.h
 //
 // Copyright (c)  2023  Xiaomi Corporation
 #ifndef SHERPA_ONNX_CSRC_ONLINE_LSTM_TRANSDUCER_MODEL_H_
@@ -28,7 +28,7 @@ class OnlineLstmTransducerModel : public OnlineTransducerModel {
   std::vector<Ort::Value> GetEncoderInitStates() override;
 
   std::pair<Ort::Value, std::vector<Ort::Value>> RunEncoder(
-      Ort::Value features, std::vector<Ort::Value> &states) override;
+      Ort::Value features, std::vector<Ort::Value> states) override;
 
   Ort::Value BuildDecoderInput(
       const std::vector<OnlineTransducerDecoderResult> &results) override;

@@ -98,7 +98,7 @@ class OnlineRecognizer::Impl {
 
     auto states = model_->StackStates(states_vec);
 
-    auto pair = model_->RunEncoder(std::move(x), states);
+    auto pair = model_->RunEncoder(std::move(x), std::move(states));
 
     decoder_->Decode(std::move(pair.first), &results);
 

@@ -23,6 +23,13 @@ struct OnlineRecognizerConfig {
   OnlineTransducerModelConfig model_config;
   std::string tokens;
 
+  OnlineRecognizerConfig() = default;
+
+  OnlineRecognizerConfig(const FeatureExtractorConfig &feat_config,
+                         const OnlineTransducerModelConfig &model_config,
+                         const std::string &tokens)
+      : feat_config(feat_config), model_config(model_config), tokens(tokens) {}
+
   std::string ToString() const;
 };
 

-// sherpa/csrc/online-transducer-decoder.h
+// sherpa-onnx/csrc/online-transducer-decoder.h
 //
 // Copyright (c)  2023  Xiaomi Corporation
 

-// sherpa/csrc/online-transducer-greedy-search-decoder.cc
+// sherpa-onnx/csrc/online-transducer-greedy-search-decoder.cc
 //
 // Copyright (c)  2023  Xiaomi Corporation
 

-// sherpa/csrc/online-transducer-greedy-search-decoder.h
+// sherpa-onnx/csrc/online-transducer-greedy-search-decoder.h
 //
 // Copyright (c)  2023  Xiaomi Corporation
 

-// sherpa/csrc/online-transducer-model-config.cc
+// sherpa-onnx/csrc/online-transducer-model-config.cc
 //
 // Copyright (c)  2023  Xiaomi Corporation
 #include "sherpa-onnx/csrc/online-transducer-model-config.h"

-// sherpa/csrc/online-transducer-model-config.h
+// sherpa-onnx/csrc/online-transducer-model-config.h
 //
 // Copyright (c)  2023  Xiaomi Corporation
 #ifndef SHERPA_ONNX_CSRC_ONLINE_TRANSDUCER_MODEL_CONFIG_H_
@@ -15,6 +15,17 @@ struct OnlineTransducerModelConfig {
   int32_t num_threads;
   bool debug = false;
 
+  OnlineTransducerModelConfig() = default;
+  OnlineTransducerModelConfig(const std::string &encoder_filename,
+                              const std::string &decoder_filename,
+                              const std::string &joiner_filename,
+                              int32_t num_threads, bool debug)
+      : encoder_filename(encoder_filename),
+        decoder_filename(decoder_filename),
+        joiner_filename(joiner_filename),
+        num_threads(num_threads),
+        debug(debug) {}
+
   std::string ToString() const;
 };
 

-// sherpa/csrc/online-transducer-model.cc
+// sherpa-onnx/csrc/online-transducer-model.cc
 //
 // Copyright (c)  2023  Xiaomi Corporation
 #include "sherpa-onnx/csrc/online-transducer-model.h"

-// sherpa/csrc/online-transducer-model.h
+// sherpa-onnx/csrc/online-transducer-model.h
 //
 // Copyright (c)  2023  Xiaomi Corporation
 #ifndef SHERPA_ONNX_CSRC_ONLINE_TRANSDUCER_MODEL_H_
@@ -59,7 +59,7 @@ class OnlineTransducerModel {
    */
   virtual std::pair<Ort::Value, std::vector<Ort::Value>> RunEncoder(
       Ort::Value features,
-      std::vector<Ort::Value> &states) = 0;  // NOLINT
+      std::vector<Ort::Value> states) = 0;  // NOLINT
 
   virtual Ort::Value BuildDecoderInput(
       const std::vector<OnlineTransducerDecoderResult> &results) = 0;

-// sherpa/csrc/onnx-utils.cc
+// sherpa-onnx/csrc/onnx-utils.cc
 //
 // Copyright (c)  2023  Xiaomi Corporation
 #include "sherpa-onnx/csrc/onnx-utils.h"

-// sherpa/csrc/onnx-utils.h
+// sherpa-onnx/csrc/onnx-utils.h
 //
 // Copyright (c)  2023  Xiaomi Corporation
 #ifndef SHERPA_ONNX_CSRC_ONNX_UTILS_H_

-// sherpa-onnx/csrc/show-onnx-info.cc
-//
-// Copyright (c)  2022-2023  Xiaomi Corporation
-
-#include <iostream>
-#include <sstream>
-
-#include "onnxruntime_cxx_api.h"  // NOLINT
-
-int main() {
-  std::cout << "ORT_API_VERSION: " << ORT_API_VERSION << "\n";
-  std::vector<std::string> providers = Ort::GetAvailableProviders();
-  std::ostringstream os;
-  os << "Available providers: ";
-  std::string sep = "";
-  for (const auto &p : providers) {
-    os << sep << p;
-    sep = ", ";
-  }
-  std::cout << os.str() << "\n";
-  return 0;
-}

-// sherpa-onnx/csrc/symbol-table.cc
+// sherpa-onnx/csrc/symbol-table.h
 //
 // Copyright (c)  2022-2023  Xiaomi Corporation
 

-// sherpa/csrc/wave-reader.cc
+// sherpa-onnx/csrc/wave-reader.cc
 //
 // Copyright (c)  2023  Xiaomi Corporation
 

-// sherpa/csrc/wave-reader.h
+// sherpa-onnx/csrc/wave-reader.h
 //
 // Copyright (c)  2023  Xiaomi Corporation
 

+add_subdirectory(csrc)
+
+if(SHERPA_ONNX_ENABLE_TESTS)
+  add_subdirectory(tests)
+endif()

+include_directories(${CMAKE_SOURCE_DIR})
+
+pybind11_add_module(_sherpa_onnx
+  features.cc
+  online-transducer-model-config.cc
+  sherpa-onnx.cc
+  online-stream.cc
+  online-recognizer.cc
+)
+
+if(APPLE)
+  execute_process(
+    COMMAND "${PYTHON_EXECUTABLE}" -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())"
+    OUTPUT_STRIP_TRAILING_WHITESPACE
+    OUTPUT_VARIABLE PYTHON_SITE_PACKAGE_DIR
+  )
+  message(STATUS "PYTHON_SITE_PACKAGE_DIR: ${PYTHON_SITE_PACKAGE_DIR}")
+  target_link_libraries(_sherpa_onnx PRIVATE "-Wl,-rpath,${PYTHON_SITE_PACKAGE_DIR}")
+endif()
+
+if(NOT WIN32)
+  target_link_libraries(_sherpa_onnx PRIVATE "-Wl,-rpath,${SHERPA_ONNX_RPATH_ORIGIN}/sherpa_onnx/lib")
+endif()
+
+target_link_libraries(_sherpa_onnx PRIVATE sherpa-onnx-core)
+
+install(TARGETS _sherpa_onnx
+  DESTINATION ../
+)

+// sherpa-onnx/python/csrc/features.cc
+//
+// Copyright (c)  2023  Xiaomi Corporation
+
+#include "sherpa-onnx/python/csrc/features.h"
+
+#include "sherpa-onnx/csrc/features.h"
+
+namespace sherpa_onnx {
+
+static void PybindFeatureExtractorConfig(py::module *m) {
+  using PyClass = FeatureExtractorConfig;
+  py::class_<PyClass>(*m, "FeatureExtractorConfig")
+      .def(py::init<float, int32_t>(), py::arg("sampling_rate") = 16000,
+           py::arg("feature_dim") = 80)
+      .def_readwrite("sampling_rate", &PyClass::sampling_rate)
+      .def_readwrite("feature_dim", &PyClass::feature_dim)
+      .def("__str__", &PyClass::ToString);
+}
+
+void PybindFeatures(py::module *m) { PybindFeatureExtractorConfig(m); }
+
+}  // namespace sherpa_onnx

+// sherpa-onnx/python/csrc/features.h
+//
+// Copyright (c)  2023  Xiaomi Corporation
+
+#ifndef SHERPA_ONNX_PYTHON_CSRC_FEATURES_H_
+#define SHERPA_ONNX_PYTHON_CSRC_FEATURES_H_
+
+#include "sherpa-onnx/python/csrc/sherpa-onnx.h"
+
+namespace sherpa_onnx {
+
+void PybindFeatures(py::module *m);
+
+}
+
+#endif  // SHERPA_ONNX_PYTHON_CSRC_FEATURES_H_

+// sherpa-onnx/python/csrc/online-recongizer.cc
+//
+// Copyright (c)  2023  Xiaomi Corporation
+
+#include "sherpa-onnx/python/csrc/online-recognizer.h"
+
+#include <string>
+#include <vector>
+
+#include "sherpa-onnx/csrc/online-recognizer.h"
+
+namespace sherpa_onnx {
+
+static void PybindOnlineRecognizerResult(py::module *m) {
+  using PyClass = OnlineRecognizerResult;
+  py::class_<PyClass>(*m, "OnlineRecognizerResult")
+      .def_property_readonly("text", [](PyClass &self) { return self.text; });
+}
+
+static void PybindOnlineRecognizerConfig(py::module *m) {
+  using PyClass = OnlineRecognizerConfig;
+  py::class_<PyClass>(*m, "OnlineRecognizerConfig")
+      .def(py::init<const FeatureExtractorConfig &,
+                    const OnlineTransducerModelConfig &, const std::string &>(),
+           py::arg("feat_config"), py::arg("model_config"), py::arg("tokens"))
+      .def_readwrite("feat_config", &PyClass::feat_config)
+      .def_readwrite("model_config", &PyClass::model_config)
+      .def_readwrite("tokens", &PyClass::tokens)
+      .def("__str__", &PyClass::ToString);
+}
+
+void PybindOnlineRecognizer(py::module *m) {
+  PybindOnlineRecognizerResult(m);
+  PybindOnlineRecognizerConfig(m);
+
+  using PyClass = OnlineRecognizer;
+  py::class_<PyClass>(*m, "OnlineRecognizer")
+      .def(py::init<const OnlineRecognizerConfig &>(), py::arg("config"))
+      .def("create_stream", &PyClass::CreateStream)
+      .def("is_ready", &PyClass::IsReady)
+      .def("decode_stream", &PyClass::DecodeStream)
+      .def("decode_streams",
+           [](PyClass &self, std::vector<OnlineStream *> ss) {
+             self.DecodeStreams(ss.data(), ss.size());
+           })
+      .def("get_result", &PyClass::GetResult);
+}
+
+}  // namespace sherpa_onnx

+// sherpa-onnx/python/csrc/online-recongizer.h
+//
+// Copyright (c)  2023  Xiaomi Corporation
+
+#ifndef SHERPA_ONNX_PYTHON_CSRC_ONLINE_RECOGNIZER_H_
+#define SHERPA_ONNX_PYTHON_CSRC_ONLINE_RECOGNIZER_H_
+
+#include "sherpa-onnx/python/csrc/sherpa-onnx.h"
+
+namespace sherpa_onnx {
+
+void PybindOnlineRecognizer(py::module *m);
+
+}
+
+#endif  // SHERPA_ONNX_PYTHON_CSRC_ONLINE_RECOGNIZER_H_

+// sherpa-onnx/python/csrc/online-stream.cc
+//
+// Copyright (c)  2023  Xiaomi Corporation
+
+#include "sherpa-onnx/python/csrc/online-stream.h"
+
+#include "sherpa-onnx/csrc/online-stream.h"
+
+namespace sherpa_onnx {
+
+void PybindOnlineStream(py::module *m) {
+  using PyClass = OnlineStream;
+  py::class_<PyClass>(*m, "OnlineStream")
+      .def("accept_waveform",
+           [](PyClass &self, float sample_rate, py::array_t<float> waveform) {
+             self.AcceptWaveform(sample_rate, waveform.data(), waveform.size());
+           })
+      .def("input_finished", &PyClass::InputFinished);
+}
+
+}  // namespace sherpa_onnx

+// sherpa-onnx/python/csrc/online-stream.h
+//
+// Copyright (c)  2023  Xiaomi Corporation
+
+#ifndef SHERPA_ONNX_PYTHON_CSRC_ONLINE_STREAM_H_
+#define SHERPA_ONNX_PYTHON_CSRC_ONLINE_STREAM_H_
+
+#include "sherpa-onnx/python/csrc/sherpa-onnx.h"
+
+namespace sherpa_onnx {
+
+void PybindOnlineStream(py::module *m);
+
+}
+
+#endif  // SHERPA_ONNX_PYTHON_CSRC_ONLINE_STREAM_H_

+// sherpa-onnx/python/csrc/online-transducer-model-config.cc
+//
+// Copyright (c)  2023  Xiaomi Corporation
+
+#include "sherpa-onnx/csrc/online-transducer-model-config.h"
+
+#include <string>
+
+#include "sherpa-onnx/python/csrc/online-transducer-model-config.h"
+
+namespace sherpa_onnx {
+
+void PybindOnlineTransducerModelConfig(py::module *m) {
+  using PyClass = OnlineTransducerModelConfig;
+  py::class_<PyClass>(*m, "OnlineTransducerModelConfig")
+      .def(py::init<const std::string &, const std::string &,
+                    const std::string &, int32_t, bool>(),
+           py::arg("encoder_filename"), py::arg("decoder_filename"),
+           py::arg("joiner_filename"), py::arg("num_threads"),
+           py::arg("debug") = false)
+      .def_readwrite("encoder_filename", &PyClass::encoder_filename)
+      .def_readwrite("decoder_filename", &PyClass::decoder_filename)
+      .def_readwrite("joiner_filename", &PyClass::joiner_filename)
+      .def_readwrite("num_threads", &PyClass::num_threads)
+      .def_readwrite("debug", &PyClass::debug)
+      .def("__str__", &PyClass::ToString);
+}
+
+}  // namespace sherpa_onnx

+// sherpa-onnx/python/csrc/online-transducer-model-config.h
+//
+// Copyright (c)  2023  Xiaomi Corporation
+
+#ifndef SHERPA_ONNX_PYTHON_CSRC_ONLINE_TRANSDUCER_MODEL_CONFIG_H_
+#define SHERPA_ONNX_PYTHON_CSRC_ONLINE_TRANSDUCER_MODEL_CONFIG_H_
+
+#include "sherpa-onnx/python/csrc/sherpa-onnx.h"
+
+namespace sherpa_onnx {
+
+void PybindOnlineTransducerModelConfig(py::module *m);
+
+}
+
+#endif  // SHERPA_ONNX_PYTHON_CSRC_ONLINE_TRANSDUCER_MODEL_CONFIG_H_

+// sherpa-onnx/python/csrc/sherpa-onnx.cc
+//
+// Copyright (c)  2023  Xiaomi Corporation
+
+#include "sherpa-onnx/python/csrc/sherpa-onnx.h"
+
+#include "sherpa-onnx/python/csrc/features.h"
+#include "sherpa-onnx/python/csrc/online-recognizer.h"
+#include "sherpa-onnx/python/csrc/online-stream.h"
+#include "sherpa-onnx/python/csrc/online-transducer-model-config.h"
+
+namespace sherpa_onnx {
+
+PYBIND11_MODULE(_sherpa_onnx, m) {
+  m.doc() = "pybind11 binding of sherpa-onnx";
+  PybindFeatures(&m);
+  PybindOnlineTransducerModelConfig(&m);
+  PybindOnlineStream(&m);
+  PybindOnlineRecognizer(&m);
+}
+
+}  // namespace sherpa_onnx

+// sherpa-onnx/python/csrc/sherpa-onnx.h
+//
+// Copyright (c)  2023  Xiaomi Corporation
+
+#ifndef SHERPA_ONNX_PYTHON_CSRC_SHERPA_ONNX_H_
+#define SHERPA_ONNX_PYTHON_CSRC_SHERPA_ONNX_H_
+
+#include "pybind11/numpy.h"
+#include "pybind11/pybind11.h"
+#include "pybind11/stl.h"
+
+namespace py = pybind11;
+
+#endif  // SHERPA_ONNX_PYTHON_CSRC_SHERPA_ONNX_H_

+from _sherpa_onnx import (
+    FeatureExtractorConfig,
+    OnlineRecognizerConfig,
+    OnlineStream,
+    OnlineTransducerModelConfig,
+)
+
+from .online_recognizer import OnlineRecognizer

+from pathlib import Path
+from typing import List
+
+from _sherpa_onnx import (
+    OnlineStream,
+    OnlineTransducerModelConfig,
+    FeatureExtractorConfig,
+    OnlineRecognizerConfig,
+)
+from _sherpa_onnx import OnlineRecognizer as _Recognizer
+
+
+def _assert_file_exists(f: str):
+    assert Path(f).is_file(), f"{f} does not exist"
+
+
+class OnlineRecognizer(object):
+    """A class for streaming speech recognition."""
+
+    def __init__(
+        self,
+        tokens: str,
+        encoder: str,
+        decoder: str,
+        joiner: str,
+        num_threads: int = 4,
+        sample_rate: float = 16000,
+        feature_dim: int = 80,
+    ):
+        """
+        Please refer to
+        `<https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html>`_
+        to download pre-trained models for different languages, e.g., Chinese,
+        English, etc.
+
+        Args:
+          tokens:
+            Path to ``tokens.txt``. Each line in ``tokens.txt`` contains two
+            columns::
+
+                symbol integer_id
+
+          encoder:
+            Path to ``encoder.onnx``.
+          decoder:
+            Path to ``decoder.onnx``.
+          joiner:
+            Path to ``joiner.onnx``.
+          num_threads:
+            Number of threads for neural network computation.
+          sample_rate:
+            Sample rate of the training data used to train the model.
+          feature_dim:
+            Dimension of the feature used to train the model.
+        """
+        _assert_file_exists(tokens)
+        _assert_file_exists(encoder)
+        _assert_file_exists(decoder)
+        _assert_file_exists(joiner)
+
+        assert num_threads > 0, num_threads
+
+        model_config = OnlineTransducerModelConfig(
+            encoder_filename=encoder,
+            decoder_filename=decoder,
+            joiner_filename=joiner,
+            num_threads=num_threads,
+        )
+
+        feat_config = FeatureExtractorConfig(
+            sampling_rate=sample_rate,
+            feature_dim=feature_dim,
+        )
+
+        recognizer_config = OnlineRecognizerConfig(
+            feat_config=feat_config,
+            model_config=model_config,
+            tokens=tokens,
+        )
+
+        self.recognizer = _Recognizer(recognizer_config)
+
+    def create_stream(self):
+        return self.recognizer.create_stream()
+
+    def decode_stream(self, s: OnlineStream):
+        self.recognizer.decode_stream(s)
+
+    def decode_streams(self, ss: List[OnlineStream]):
+        self.recognizer.decode_streams(ss)
+
+    def is_ready(self, s: OnlineStream) -> bool:
+        return self.recognizer.is_ready(s)
+
+    def get_result(self, s: OnlineStream) -> str:
+        return self.recognizer.get_result(s).text

+function(sherpa_onnx_add_py_test source)
+  get_filename_component(name ${source} NAME_WE)
+  set(name "${name}_py")
+
+  add_test(NAME ${name}
+    COMMAND
+      "${PYTHON_EXECUTABLE}"
+      "${CMAKE_CURRENT_SOURCE_DIR}/${source}"
+  )
+
+  get_filename_component(sherpa_onnx_path ${CMAKE_CURRENT_LIST_DIR} DIRECTORY)
+
+  set_property(TEST ${name}
+    PROPERTY ENVIRONMENT "PYTHONPATH=${sherpa_path}:$<TARGET_FILE_DIR:_sherpa_onnx>:$ENV{PYTHONPATH}"
+  )
+endfunction()
+
+# please sort the files in alphabetic order
+set(py_test_files
+  test_feature_extractor_config.py
+  test_online_transducer_model_config.py
+)
+
+foreach(source IN LISTS py_test_files)
+  sherpa_onnx_add_py_test(${source})
+endforeach()
+

+# sherpa-onnx/python/tests/test_feature_extractor_config.py
+#
+# Copyright (c)  2023  Xiaomi Corporation
+#
+# To run this single test, use
+#
+#  ctest --verbose -R  test_feature_extractor_config_py
+
+import unittest
+
+import sherpa_onnx
+
+
+class TestFeatureExtractorConfig(unittest.TestCase):
+    def test_default_constructor(self):
+        config = sherpa_onnx.FeatureExtractorConfig()
+        assert config.sampling_rate == 16000, config.sampling_rate
+        assert config.feature_dim == 80, config.feature_dim
+        print(config)
+
+    def test_constructor(self):
+        config = sherpa_onnx.FeatureExtractorConfig(sampling_rate=8000, feature_dim=40)
+        assert config.sampling_rate == 8000, config.sampling_rate
+        assert config.feature_dim == 40, config.feature_dim
+        print(config)
+
+
+if __name__ == "__main__":
+    unittest.main()

+# sherpa-onnx/python/tests/test_online_transducer_model_config.py
+#
+# Copyright (c)  2023  Xiaomi Corporation
+#
+# To run this single test, use
+#
+#  ctest --verbose -R  test_online_transducer_model_config_py
+
+import unittest
+
+import sherpa_onnx
+
+
+class TestOnlineTransducerModelConfig(unittest.TestCase):
+    def test_constructor(self):
+        config = sherpa_onnx.OnlineTransducerModelConfig(
+            encoder_filename="encoder.onnx",
+            decoder_filename="decoder.onnx",
+            joiner_filename="joiner.onnx",
+            num_threads=8,
+            debug=True,
+        )
+        assert config.encoder_filename == "encoder.onnx", config.encoder_filename
+        assert config.decoder_filename == "decoder.onnx", config.decoder_filename
+        assert config.joiner_filename == "joiner.onnx", config.joiner_filename
+        assert config.num_threads == 8, config.num_threads
+        assert config.debug is True, config.debug
+        print(config)
+
+
+if __name__ == "__main__":
+    unittest.main()