feat: Download Vosk model with sprc download vosk

.github/workflows/unittests.yml

@@ -57,7 +57,7 @@ jobs:
         run: |
           python -m pip install .[dev,whisper-local,faster-whisper,google-cloud,openai,groq,vosk]
       - name: Set up vosk model
-        run: pipx run setup_vosk.py
+        run: sprc download vosk
       - name: Test with unittest
         run: |
           pytest --doctest-modules -v speech_recognition/recognizers/ tests/

README.rst

@@ -59,8 +59,6 @@ The `library reference <https://github.com/Uberi/speech_recognition/blob/master/
 
 See `Notes on using PocketSphinx <https://github.com/Uberi/speech_recognition/blob/master/reference/pocketsphinx.rst>`__ for information about installing languages, compiling PocketSphinx, and building language packs from online resources. This document is also included under ``reference/pocketsphinx.rst``.
 
-You have to install Vosk models for using Vosk. `Here <https://alphacephei.com/vosk/models>`__ are models avaiable. You have to place them in models folder of your project, like "your-project-folder/models/your-vosk-model"
-
 Examples
 --------
 
@@ -146,7 +144,8 @@ You can install it with ``python3 -m pip install SpeechRecognition[vosk]``.
 
 You also have to install Vosk Models:
 
-`Here <https://alphacephei.com/vosk/models>`__ are models avaiable for download. You have to place them in models folder of your project, like "your-project-folder/models/your-vosk-model"
+`Here <https://alphacephei.com/vosk/models>`__ are models available for download. You have to place them in the ``model`` directory of your project, like "your-project-folder/model".
+You can also run ``sprc download vosk`` to download the default model.
 
 Google Cloud Speech Library for Python (for Google Cloud Speech-to-Text API users)
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

setup.py

@@ -75,4 +75,7 @@ def run(self):
         "standard-aifc; python_version>='3.13'",
         "audioop-lts; python_version>='3.13'",
     ],
+    entry_points={
+        "console_scripts": ["sprc=speech_recognition.cli:main"],
+    },
 )

speech_recognition/cli.py

@@ -0,0 +1,69 @@
+import argparse
+import os
+import shutil
+import tempfile
+import zipfile
+from urllib.request import urlopen
+
+from tqdm import tqdm
+
+
+def download_vosk_model(url: str, model_dir: str) -> None:
+    model_filename = os.path.basename(url)
+    model_name = os.path.splitext(model_filename)[0]
+
+    print(f"Downloading model {model_filename} ...")
+    with urlopen(url) as response:
+        total_size = int(response.headers.get("Content-Length", 0))
+        with tempfile.TemporaryDirectory() as temp_dir:
+            download_path = os.path.join(temp_dir, model_filename)
+            with open(download_path, "wb") as f, tqdm(
+                total=total_size, unit="B", unit_scale=True
+            ) as pbar:
+                while True:
+                    chunk = response.read(8192)
+                    if not chunk:
+                        break
+                    f.write(chunk)
+                    pbar.update(len(chunk))
+
+            print("Unzip model...")
+            with zipfile.ZipFile(download_path, "r") as zip_ref:
+                zip_ref.extractall(temp_dir)
+
+            extracted_dir = os.path.join(temp_dir, model_name)
+            if os.path.exists(model_dir):
+                shutil.rmtree(model_dir)
+            shutil.copytree(extracted_dir, model_dir)
+
+    print(f"Setup complete! Model is placed in the directory: {model_dir}")
+
+
+def main(argv=None) -> None:
+    parser = argparse.ArgumentParser(prog="sprc")
+    subparsers = parser.add_subparsers(dest="command")
+
+    download_parser = subparsers.add_parser("download")
+    download_subparsers = download_parser.add_subparsers(dest="target")
+
+    vosk_parser = download_subparsers.add_parser("vosk")
+    vosk_parser.add_argument(
+        "--url",
+        default="https://alphacephei.com/vosk/models/vosk-model-small-en-us-0.15.zip",
+    )
+    vosk_parser.add_argument("--dir", default="model")
+
+    def _download_vosk(args):
+        download_vosk_model(args.url, args.dir)
+
+    vosk_parser.set_defaults(func=_download_vosk)
+
+    args = parser.parse_args(argv)
+    if hasattr(args, "func"):
+        args.func(args)
+    else:
+        parser.print_help()
+
+
+if __name__ == "__main__":
+    main()