⚡️ Switch to faster-whisper

backend/transcribee_backend/models/task.py

@@ -179,7 +179,11 @@ def from_orm(cls, task: Task, update={}) -> Self:
             id=task.id,
             state=task.state,
             dependencies=[x.dependant_on_id for x in task.dependency_links],
-            current_attempt=None,
+            current_attempt=(
+                TaskAttemptResponse.from_orm(task.current_attempt)
+                if task.current_attempt is not None
+                else None
+            ),
             document_id=task.document_id,
             task_type=task.task_type,
             task_parameters=task.task_parameters,

backend/transcribee_backend/routers/document.py

@@ -282,20 +282,12 @@ def create_default_tasks_for_document(
     )
     session.add(transcribe_task)
 
-    align_task = Task(
-        task_type=TaskType.ALIGN,
-        task_parameters={},
-        document_id=document.id,
-        dependencies=[transcribe_task],
-    )
-    session.add(align_task)
-
     if number_of_speakers != 0 and number_of_speakers != 1:
         speaker_identification_task = Task(
             task_type=TaskType.IDENTIFY_SPEAKERS,
             task_parameters={"number_of_speakers": number_of_speakers},
             document_id=document.id,
-            dependencies=[align_task],
+            dependencies=[transcribe_task],
         )
         session.add(speaker_identification_task)
 

shell.nix

@@ -20,6 +20,8 @@ let
   });
   ld_packages = [
     pkgs.file
+    # for ctranslate2
+    pkgs.stdenv.cc.cc.lib
   ];
 
 in
@@ -67,7 +69,7 @@ pkgs.mkShell {
     # Some libraries are not found if not added directly to LD_LIBRARY_PATH / DYLD_LIBRARY_PATH (on darwin)
     # However just adding them there is not enough, because macOS purges the DYLD_* variables in some conditions
     # This means we have to set them again in some script (e.g. ./start_backend.sh) -> we need a "safe" env var to pass them to the script
-    export TRANSCRIBEE_DYLD_LIBRARY_PATH=${builtins.concatStringsSep ":" (map (x: x + "/lib") ld_packages)}
+    export TRANSCRIBEE_DYLD_LIBRARY_PATH=${pkgs.lib.makeLibraryPath ld_packages}
     export LD_LIBRARY_PATH=$LD_SEARCH_PATH:$TRANSCRIBEE_DYLD_LIBRARY_PATH
   '' + pkgs.lib.optionalString pkgs.stdenv.isDarwin ''
     export CPPFLAGS="-I${pkgs.libcxx.dev}/include/c++/v1"

worker/pyproject.toml

@@ -17,13 +17,13 @@ dependencies = [
     "torch>=2.0.0",
     "automerge @ git+https://github.com/transcribee/automerge-py.git@057303bd087401f12b166e2adb7161f0fcb3a9dc",
     "websockets>=10.4",
-    "whispercppy>=0.0.4",
     "scikit-learn>=1.2.2",
     "watchfiles>=0.19.0",
     "speechbrain>=0.5.14",
     "ffmpeg-python>=0.2.0",
     "transcribee-proto @ file:///${PROJECT_ROOT}/../proto",
     "PyICU>=2.11",
+    "faster-whisper>=0.10.0",
 ]
 
 requires-python = ">=3.10"
@@ -45,6 +45,8 @@ build-backend = "pdm.pep517.api"
 soundfile = "0.11.0"
 
 
+
+
 [[tool.pdm.source]]
 type = "find_links"
 url = "https://download.pytorch.org/whl/cpu/torch_stable.html"

worker/scripts/generate_model_config.py

@@ -3,12 +3,9 @@
 import re
 from typing import List
 
+from faster_whisper.tokenizer import _LANGUAGE_CODES
+from faster_whisper.utils import _MODELS
 from pydantic import BaseModel
-from transcribee_worker.torchaudio_align import (
-    DEFAULT_ALIGN_MODELS_HF,
-    DEFAULT_ALIGN_MODELS_TORCH,
-)
-from transcribee_worker.whisper_transcribe import get_context
 
 
 def is_english_only(model_name):
@@ -26,37 +23,14 @@ class ModelConfig(BaseModel):
     parser.add_argument("out", type=argparse.FileType("w"))
     args = parser.parse_args()
 
-    models = [
-        "tiny.en",
-        "tiny",
-        "base.en",
-        "base",
-        "small.en",
-        "small",
-        "medium.en",
-        "medium",
-        "large-v1",
-        "large",
-    ]
-
-    alignable_languages = set(DEFAULT_ALIGN_MODELS_HF.keys()) | set(
-        DEFAULT_ALIGN_MODELS_TORCH.keys()
-    )
-
     model_configs = []
+    multilingual_model_langs = list(sorted(_LANGUAGE_CODES))
 
-    context = get_context("tiny")
-    multilingual_model_langs = set(
-        context.lang_id_to_str(i) for i in range(context.lang_max_id + 1)
-    )
-
-    for model in models:
+    for model in _MODELS:
         if is_english_only(model):
             languages = ["en"]
         else:
-            languages = ["auto"] + list(
-                sorted(multilingual_model_langs & alignable_languages)
-            )
+            languages = ["auto"] + multilingual_model_langs
 
         model_configs.append(
             ModelConfig(

worker/tests/test_transcribe.py

@@ -1,4 +1,3 @@
-import asyncio
 import glob
 from pathlib import Path
 from typing import List
@@ -7,24 +6,18 @@
 from pydantic import BaseModel, parse_file_as
 from transcribee_proto.document import Paragraph
 from transcribee_worker.whisper_transcribe import (
-    combine_tokens_to_words,
     move_space_to_prev_token,
     strict_sentence_paragraphs,
 )
 
 
-async def list_to_async_iter(list):
-    for item in list:
-        yield item
-
-
-def async_doc_chain_func_to_list(*funcs):
-    async def wrapper(input: List[Paragraph]):
+def doc_chain_func_to_list(*funcs):
+    def wrapper(input: List[Paragraph]):
         res = []
-        iter = list_to_async_iter(input)
+        iter_ = iter(input)
         for func in funcs:
-            iter = func(iter)
-        async for x in iter:
+            iter_ = func(iter_)
+        for x in iter_:
             res.append(x)
         return res
 
@@ -36,23 +29,6 @@ class SpecInput(BaseModel):
     expected: List[Paragraph]
 
 
-@pytest.mark.parametrize(
-    "data_file",
-    glob.glob(
-        str(Path(__file__).parent / "data" / "test_combine_tokens_to_words*.json"),
-    ),
-)
-def test_combine_tokens_to_words(data_file):
-    test_data = parse_file_as(SpecInput, data_file)
-
-    output = list(
-        asyncio.run(
-            async_doc_chain_func_to_list(combine_tokens_to_words)(test_data.input)
-        )
-    )
-    assert output == test_data.expected
-
-
 @pytest.mark.parametrize(
     "data_file",
     glob.glob(
@@ -62,11 +38,7 @@ def test_combine_tokens_to_words(data_file):
 def test_strict_sentence_paragraphs(data_file):
     test_data = parse_file_as(SpecInput, data_file)
 
-    output = list(
-        asyncio.run(
-            async_doc_chain_func_to_list(strict_sentence_paragraphs)(test_data.input)
-        )
-    )
+    output = list(doc_chain_func_to_list(strict_sentence_paragraphs)(test_data.input))
     assert [x.text() for x in output] == [x.text() for x in test_data.expected]
     assert output == test_data.expected
 
@@ -80,11 +52,7 @@ def test_strict_sentence_paragraphs(data_file):
 def test_move_space_to_prev_token(data_file):
     test_data = parse_file_as(SpecInput, data_file)
 
-    output = list(
-        asyncio.run(
-            async_doc_chain_func_to_list(move_space_to_prev_token)(test_data.input)
-        )
-    )
+    output = doc_chain_func_to_list(move_space_to_prev_token)(test_data.input)
     assert output == test_data.expected
 
 
@@ -97,13 +65,9 @@ def test_move_space_to_prev_token(data_file):
 def test_space_and_sentences(data_file):
     test_data = parse_file_as(SpecInput, data_file)
 
-    output = list(
-        asyncio.run(
-            async_doc_chain_func_to_list(
-                move_space_to_prev_token, strict_sentence_paragraphs
-            )(test_data.input)
-        )
-    )
+    output = doc_chain_func_to_list(
+        move_space_to_prev_token, strict_sentence_paragraphs
+    )(test_data.input)
     for p in output:
         print(p.json())
     assert output == test_data.expected