revert faster-whisper to v1.0.3

This reverts commit 6decabefae.

.dockerignore

@@ -0,0 +1 @@
+/venv

Dockerfile

@@ -0,0 +1,19 @@
+FROM docker.io/nvidia/cuda:12.0.0-cudnn8-runtime-ubuntu22.04
+
+RUN apt-get update && \
+    apt-get install -y ffmpeg python3 python3-pip git && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+
+COPY requirements.txt .
+
+RUN pip3 install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+EXPOSE 5000
+
+# 启动 whisper_fastapi.py
+ENTRYPOINT ["python3", "whisper_fastapi.py"]

requirements.txt

@@ -4,4 +4,5 @@ uvicorn[standard]
 whisper_ctranslate2
 opencc
 prometheus-fastapi-instrumentator
+git+https://github.com/heimoshuiyu/faster-whisper@prompt
 pydub

requirements_version.txt

@@ -1,48 +1,49 @@
-annotated-types==0.6.0
-anyio==3.7.1
-av==10.0.0
-certifi==2023.7.22
-cffi==1.16.0
-charset-normalizer==3.3.2
-click==8.1.7
-coloredlogs==15.0.1
-ctranslate2==3.21.0
-fastapi==0.104.1
-faster-whisper==0.9.0
-filelock==3.13.1
-flatbuffers==23.5.26
-fsspec==2023.10.0
-h11==0.14.0
-httptools==0.6.1
-huggingface-hub==0.17.3
-humanfriendly==10.0
-idna==3.4
-mpmath==1.3.0
-numpy==1.26.2
-onnxruntime==1.16.2
-OpenCC==1.1.7
-packaging==23.2
-prometheus-client==0.18.0
-prometheus-fastapi-instrumentator==6.1.0
-protobuf==4.25.0
-pycparser==2.21
-pydantic==2.5.0
-pydantic_core==2.14.1
-pydub==0.25.1
-python-dotenv==1.0.0
-python-multipart==0.0.6
-PyYAML==6.0.1
-requests==2.31.0
-sniffio==1.3.0
-sounddevice==0.4.6
-starlette==0.27.0
-sympy==1.12
-tokenizers==0.14.1
-tqdm==4.66.1
-typing_extensions==4.8.0
-urllib3==2.1.0
-uvicorn==0.24.0.post1
-uvloop==0.19.0
-watchfiles==0.21.0
-websockets==12.0
-whisper-ctranslate2==0.3.2
+annotated-types==0.7.0
+anyio==4.4.0
+av==12.3.0
+certifi==2024.8.30
+cffi==1.17.1
+charset-normalizer==3.3.2
+click==8.1.7
+coloredlogs==15.0.1
+ctranslate2==4.4.0
+exceptiongroup==1.2.2
+fastapi==0.114.1
+faster-whisper @ git+https://github.com/heimoshuiyu/faster-whisper@28a4d11a736d8cdeb4655ee5d7e4b4e7ae5ec8e0
+filelock==3.16.0
+flatbuffers==24.3.25
+fsspec==2024.9.0
+h11==0.14.0
+httptools==0.6.1
+huggingface-hub==0.24.6
+humanfriendly==10.0
+idna==3.8
+mpmath==1.3.0
+numpy==2.1.1
+onnxruntime==1.19.2
+OpenCC==1.1.9
+packaging==24.1
+prometheus-fastapi-instrumentator==7.0.0
+prometheus_client==0.20.0
+protobuf==5.28.0
+pycparser==2.22
+pydantic==2.9.1
+pydantic_core==2.23.3
+pydub==0.25.1
+python-dotenv==1.0.1
+python-multipart==0.0.9
+PyYAML==6.0.2
+requests==2.32.3
+sniffio==1.3.1
+sounddevice==0.5.0
+starlette==0.38.5
+sympy==1.13.2
+tokenizers==0.20.0
+tqdm==4.66.5
+typing_extensions==4.12.2
+urllib3==2.2.2
+uvicorn==0.30.6
+uvloop==0.20.0
+watchfiles==0.24.0
+websockets==13.0.1
+whisper-ctranslate2==0.4.5

start-docker.sh

@@ -0,0 +1,10 @@
+#!/bin/bash
+
+docker run -d --name whisper-fastapi \
+    --restart unless-stopped \
+    --name whisper-fastapi \
+    -v ~/.cache/huggingface:/root/.cache/huggingface \
+    --gpus all \
+    -p 5000:5000 \
+    docker.io/heimoshuiyu/whisper-fastapi:latest \
+    --model large-v2

start-podman.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+
+podman run -d --name whisper-fastapi \
+    --restart unless-stopped \
+    --name whisper-fastapi \
+    -v ~/.cache/huggingface:/root/.cache/huggingface \
+    --device nvidia.com/gpu=all --security-opt=label=disable \
+    --gpus all \
+    -p 5000:5000 \
+    docker.io/heimoshuiyu/whisper-fastapi:latest \
+    --model large-v2

whisper_fastapi.py

@@ -1,4 +1,3 @@
-from faster_whisper import vad
 import tqdm
 import json
 from fastapi.responses import StreamingResponse
@@ -8,7 +7,7 @@ import io
 import hashlib
 import argparse
 import uvicorn
-from typing import Annotated, Any, BinaryIO, Literal, Generator
+from typing import Annotated, Any, BinaryIO, Literal, Generator, Tuple, Iterable
 from fastapi import (
     File,
     HTTPException,
@@ -22,32 +21,35 @@ from fastapi import (
 from fastapi.middleware.cors import CORSMiddleware
 from src.whisper_ctranslate2.whisper_ctranslate2 import Transcribe
 from src.whisper_ctranslate2.writers import format_timestamp
+from faster_whisper.transcribe import Segment, TranscriptionInfo
 import opencc
 from prometheus_fastapi_instrumentator import Instrumentator
 
 parser = argparse.ArgumentParser()
 parser.add_argument("--host", default="0.0.0.0", type=str)
 parser.add_argument("--port", default=5000, type=int)
-parser.add_argument("--model", default="large-v2", type=str)
+parser.add_argument("--model", default="large-v3", type=str)
 parser.add_argument("--device", default="auto", type=str)
 parser.add_argument("--cache_dir", default=None, type=str)
+parser.add_argument("--local_files_only", default=False, type=bool)
+parser.add_argument("--threads", default=4, type=int)
 args = parser.parse_args()
 app = FastAPI()
 # Instrument your app with default metrics and expose the metrics
 Instrumentator().instrument(app).expose(app, endpoint="/konele/metrics")
 ccc = opencc.OpenCC("t2s.json")
 
-print("Loading model...")
+print(f"Loading model to device {args.device}...")
 transcriber = Transcribe(
     model_path=args.model,
     device=args.device,
     device_index=0,
     compute_type="default",
-    threads=1,
+    threads=args.threads,
     cache_directory=args.cache_dir,
-    local_files_only=False,
+    local_files_only=args.local_files_only,
 )
-print("Model loaded!")
+print(f"Model loaded to device {transcriber.model.model.device}")
 
 
 # allow all cors
@@ -76,7 +78,7 @@ def tsv_writer(generator: Generator[dict[str, Any], Any, None]):
     for i, segment in enumerate(generator):
         start_time = str(round(1000 * segment["start"]))
         end_time = str(round(1000 * segment["end"]))
-        text = segment["text"]
+        text = segment["text"].strip()
         yield f"{start_time}\t{end_time}\t{text}\n"
 
 
@@ -88,7 +90,7 @@ def srt_writer(generator: Generator[dict[str, Any], Any, None]):
         end_time = format_timestamp(
             segment["end"], decimal_marker=",", always_include_hours=True
         )
-        text = segment["text"]
+        text = segment["text"].strip()
         yield f"{i}\n{start_time} --> {end_time}\n{text}\n\n"
 
 
@@ -97,15 +99,16 @@ def vtt_writer(generator: Generator[dict[str, Any], Any, None]):
     for i, segment in enumerate(generator):
         start_time = format_timestamp(segment["start"])
         end_time = format_timestamp(segment["end"])
-        text = segment["text"]
+        text = segment["text"].strip()
         yield f"{start_time} --> {end_time}\n{text}\n\n"
 
 
 def build_json_result(
-    generator: Generator[dict[str, Any], Any, None]
+    generator: Iterable[Segment],
+    info:  dict,
 ) -> dict[str, Any]:
     segments = [i for i in generator]
-    return {
+    return info | {
         "text": "\n".join(i["text"] for i in segments),
         "segments": segments,
     }
@@ -117,50 +120,47 @@ def stream_builder(
     vad_filter: bool,
     language: str | None,
     initial_prompt: str = "",
-):
+    repetition_penalty: float = 1.0,
+) -> Tuple[Iterable[dict], dict]:
     segments, info = transcriber.model.transcribe(
         audio=audio,
         language=language,
         task=task,
-        beam_size=5,
-        best_of=5,
-        patience=1.0,
-        length_penalty=-1.0,
-        repetition_penalty=1.0,
-        no_repeat_ngram_size=0,
-        temperature=[0.0, 1.0 + 1e-6, 0.2],
-        compression_ratio_threshold=2.4,
-        log_prob_threshold=-1.0,
-        no_speech_threshold=0.6,
-        condition_on_previous_text=True,
-        prompt_reset_on_temperature=False,
         initial_prompt=initial_prompt,
-        suppress_blank=False,
-        suppress_tokens=[],
         word_timestamps=True,
-        prepend_punctuations="\"'“¿([{-",
-        append_punctuations="\"'.。,，!！?？:：”)]}、",
-        vad_filter=vad_filter,
-        vad_parameters=None,
+        repetition_penalty=repetition_penalty,
     )
     print(
         "Detected language '%s' with probability %f"
         % (info.language, info.language_probability)
     )
-    last_pos = 0
-    with tqdm.tqdm(total=info.duration, unit="seconds", disable=True) as pbar:
-        for segment in segments:
-            start, end, text = segment.start, segment.end, segment.text
-            pbar.update(end - last_pos)
-            last_pos = end
-            data = segment._asdict()
-            data["total"] = info.duration
-            data["text"] = ccc.convert(data["text"])
-            yield data
+    def wrap():
+        last_pos = 0
+        with tqdm.tqdm(total=info.duration, unit="seconds", disable=True) as pbar:
+            for segment in segments:
+                start, end, text = segment.start, segment.end, segment.text
+                pbar.update(end - last_pos)
+                last_pos = end
+                data = segment._asdict()
+                if data.get('words') is not None:
+                    data["words"] = [i._asdict() for i in data["words"]]
+                if info.language == "zh":
+                    data["text"] = ccc.convert(data["text"])
+                yield data
+
+    info_dict = info._asdict()
+    if info_dict['transcription_options'] is not None:
+        info_dict['transcription_options'] = info_dict['transcription_options']._asdict()
+    if info_dict['vad_options'] is not None:
+        info_dict['vad_options'] = info_dict['vad_options']._asdict()
+    
+    return wrap(), info_dict
 
 
 @app.websocket("/k6nele/status")
 @app.websocket("/konele/status")
+@app.websocket("/v1/k6nele/status")
+@app.websocket("/v1/konele/status")
 async def konele_status(
     websocket: WebSocket,
 ):
@@ -171,6 +171,8 @@ async def konele_status(
 
 @app.websocket("/k6nele/ws")
 @app.websocket("/konele/ws")
+@app.websocket("/v1/k6nele/ws")
+@app.websocket("/v1/konele/ws")
 async def konele_ws(
     websocket: WebSocket,
     task: Literal["transcribe", "translate"] = "transcribe",
@@ -184,15 +186,11 @@ async def konele_ws(
     # convert lang code format (eg. en-US to en)
     lang = lang.split("-")[0]
 
-    print("WebSocket client connected, lang is", lang)
-    print("content-type is", content_type)
     data = b""
     while True:
         try:
             data += await websocket.receive_bytes()
-            print("Received data:", len(data), data[-10:])
             if data[-3:] == b"EOS":
-                print("End of speech")
                 break
         except:
             break
@@ -215,17 +213,16 @@ async def konele_ws(
 
     file_obj.seek(0)
 
-    generator = stream_builder(
+    generator, info = stream_builder(
         audio=file_obj,
         task=task,
         vad_filter=vad_filter,
         language=None if lang == "und" else lang,
         initial_prompt=initial_prompt,
     )
-    result = build_json_result(generator)
+    result = build_json_result(generator, info)
 
     text = result.get("text", "")
-    print("result", text)
 
     await websocket.send_json(
         {
@@ -240,6 +237,8 @@ async def konele_ws(
 
 @app.post("/k6nele/post")
 @app.post("/konele/post")
+@app.post("/v1/k6nele/post")
+@app.post("/v1/konele/post")
 async def translateapi(
     request: Request,
     task: Literal["transcribe", "translate"] = "transcribe",
@@ -248,14 +247,12 @@ async def translateapi(
     vad_filter: bool = False,
 ):
     content_type = request.headers.get("Content-Type", "")
-    print("downloading request file", content_type)
 
     # convert lang code format (eg. en-US to en)
     lang = lang.split("-")[0]
 
     splited = [i.strip() for i in content_type.split(",") if "=" in i]
     info = {k: v for k, v in (i.split("=") for i in splited)}
-    print(info)
 
     channels = int(info.get("channels", "1"))
     rate = int(info.get("rate", "16000"))
@@ -279,17 +276,16 @@ async def translateapi(
 
     file_obj.seek(0)
 
-    generator = stream_builder(
+    generator, info = stream_builder(
         audio=file_obj,
         task=task,
         vad_filter=vad_filter,
         language=None if lang == "und" else lang,
         initial_prompt=initial_prompt,
     )
-    result = build_json_result(generator)
+    result = build_json_result(generator, info)
 
     text = result.get("text", "")
-    print("result", text)
 
     return {
         "status": 0,
@@ -306,6 +302,7 @@ async def transcription(
     task: str = Form("transcribe"),
     language: str = Form("und"),
     vad_filter: bool = Form(False),
+    repetition_penalty: float = Form(1.0),
 ):
     """Transcription endpoint
 
@@ -313,11 +310,12 @@ async def transcription(
     """
 
     # timestamp as filename, keep original extension
-    generator = stream_builder(
+    generator, info = stream_builder(
         audio=io.BytesIO(file.file.read()),
         task=task,
         vad_filter=vad_filter,
         language=None if language == "und" else language,
+        repetition_penalty=repetition_penalty,
     )
 
     # special function for streaming response (OpenAI API does not have this)
@@ -327,7 +325,7 @@ async def transcription(
             media_type="text/event-stream",
         )
     elif response_format == "json":
-        return build_json_result(generator)
+        return build_json_result(generator, info)
     elif response_format == "text":
         return StreamingResponse(text_writer(generator), media_type="text/plain")
     elif response_format == "tsv":