Spaces:
Sleeping
Sleeping
File size: 6,455 Bytes
402daee |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 |
from typing import Union, Annotated
import importlib.metadata
import logging
import os
import tempfile
from celery.result import AsyncResult
from fastapi import FastAPI, File, Query, Request, UploadFile, applications
from fastapi.openapi.docs import get_swagger_ui_html
from fastapi.responses import HTMLResponse, JSONResponse, PlainTextResponse, RedirectResponse, StreamingResponse
from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates
from whisper import tokenizer
import aiofiles
from .util import apierror
from .worker import transcribe
logging.basicConfig(format='[%(asctime)s] [%(name)s] [%(levelname)s] %(message)s', level=logging.INFO, force=True)
logger = logging.getLogger(__name__)
ASR_ENGINE = os.getenv("ASR_ENGINE", "faster_whisper")
ASR_OPTIONS = frozenset([
"task",
"language",
"initial_prompt",
"encode",
"output",
"vad_filter",
"word_timestamps",
"model_name",
])
DEFAULT_MODEL_NAME = os.getenv("ASR_MODEL", "small")
LANGUAGE_CODES = sorted(list(tokenizer.LANGUAGES.keys()))
projectMetadata = importlib.metadata.metadata('reaspeech')
app = FastAPI(
# docs_url=None,
# redoc_url=None,
title=projectMetadata['Name'].title().replace('-', ' '),
description=projectMetadata['Summary'],
version=projectMetadata['Version'],
contact={
"url": projectMetadata['Home-page']
},
swagger_ui_parameters={"defaultModelsExpandDepth": -1},
license_info={
"name": "MIT License",
"url": projectMetadata['License']
}
)
assets_path = os.getcwd() + "/swagger-ui-assets"
if os.path.exists(assets_path + "/swagger-ui.css") and os.path.exists(assets_path + "/swagger-ui-bundle.js"):
app.mount("/assets", StaticFiles(directory=assets_path), name="static")
def swagger_monkey_patch(*args, **kwargs):
return get_swagger_ui_html(
*args,
**kwargs,
swagger_favicon_url="",
swagger_css_url="/assets/swagger-ui.css",
swagger_js_url="/assets/swagger-ui-bundle.js",
)
applications.get_swagger_ui_html = swagger_monkey_patch
static_path = os.getcwd() + "/app/static"
app.mount("/static", StaticFiles(directory=static_path), name="static")
templates_path = os.getcwd() + "/app/templates"
templates = Jinja2Templates(directory=templates_path)
output_directory = os.environ.get("OUTPUT_DIRECTORY", os.getcwd() + "/app/output")
output_url_prefix = os.environ.get("OUTPUT_URL_PREFIX", "/output")
app.mount(output_url_prefix, StaticFiles(directory=output_directory), name="output")
@app.exception_handler(apierror.APIError)
async def api_exception_handler(request: Request, exc: apierror.APIError):
return exc.to_response()
@app.exception_handler(500)
async def internal_exception_handler(request: Request, exc: Exception):
return apierror.error_response(exc)
@app.get("/", response_class=RedirectResponse, include_in_schema=False)
async def index():
return "/reaspeech"
@app.get("/reaspeech", response_class=HTMLResponse, include_in_schema=False)
async def reaspeech(request: Request):
return templates.TemplateResponse("index.html", {"request": request})
@app.get("/reascript", response_class=PlainTextResponse, include_in_schema=False)
async def reascript(request: Request, name: str, host: str):
return templates.TemplateResponse("reascript.lua", {
"request": request,
"name": name,
"host": host
},
media_type='application/x-lua',
headers={
'Content-Disposition': f'attachment; filename="{name}.lua"'
}
)
@app.post("/asr", tags=["Endpoints"])
async def asr(
task: Union[str, None] = Query(default="transcribe", enum=["transcribe", "translate"]),
language: Union[str, None] = Query(default=None, enum=LANGUAGE_CODES),
initial_prompt: Union[str, None] = Query(default=None),
audio_file: UploadFile = File(...),
encode: bool = Query(default=True, description="Encode audio first through ffmpeg"),
output: Union[str, None] = Query(default="txt", enum=["txt", "vtt", "srt", "tsv", "json"]),
vad_filter: Annotated[bool | None, Query(
description="Enable the voice activity detection (VAD) to filter out parts of the audio without speech",
include_in_schema=(True if ASR_ENGINE == "faster_whisper" else False)
)] = False,
word_timestamps: bool = Query(default=False, description="Word level timestamps"),
model_name: Union[str, None] = Query(default=None, description="Model name to use for transcription"),
use_async: bool = Query(default=False, description="Use asynchronous processing")
):
asr_options = {k: v for k, v in locals().items() if k in ASR_OPTIONS}
async_str = " (async)" if use_async else ""
logger.info(f"Transcribing{async_str} {audio_file.filename} with {asr_options}")
with tempfile.NamedTemporaryFile(delete=False) as temp_file:
temp_file_path = temp_file.name
async with aiofiles.open(temp_file_path, 'wb') as out_file:
while content := await audio_file.read(1024 * 1024): # Read in chunks of 1MB
await out_file.write(content)
transcriber = transcribe.si(temp_file_path, audio_file.filename, asr_options)
if use_async:
job = transcriber.apply_async()
return JSONResponse({"job_id": job.id})
else:
result = transcriber.apply().get()
def reader():
with open(result['output_path'], "r") as file:
yield from file
filename = result['output_filename']
return StreamingResponse(
reader(),
media_type="text/plain",
headers={
'Asr-Engine': ASR_ENGINE,
'Content-Disposition': f'attachment; filename="{filename}"'
})
@app.get("/jobs/{job_id}", tags=["Endpoints"])
async def job_status(job_id: str):
job = AsyncResult(job_id)
result = {
"job_id": job_id,
"job_status": job.status,
"job_result": job.result
}
if job.status == "FAILURE":
result["job_result"] = apierror.error_dict(result["job_result"])
return JSONResponse(result)
@app.delete("/jobs/{job_id}", tags=["Endpoints"])
async def revoke_job(job_id: str):
job = AsyncResult(job_id)
job.revoke(terminate=True)
result = {
"job_id": job_id,
"job_status": job.status
}
return JSONResponse(result)
|