Auto-update: Thu Jun 27 19:27:06 PDT 2024
This commit is contained in:
sanj
parent
12b4b53705
commit
6acb9e4d8e
6 changed files with 79 additions and 73 deletions
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@ -41,7 +41,7 @@ transcription_results = {}
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@asr.post("/transcribe")
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@asr.post("/v1/audio/transcription")
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async def transcribe_endpoint(
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background_tasks: BackgroundTasks,
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bg_tasks: BackgroundTasks,
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file: UploadFile = File(...),
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params: str = Form(...)
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):
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@ -58,7 +58,7 @@ async def transcribe_endpoint(
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temp_file.write(await file.read())
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temp_file_path = temp_file.name
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transcription_job = await transcribe_audio(file_path=temp_file_path, params=parameters, background_tasks=background_tasks)
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transcription_job = await transcribe_audio(file_path=temp_file_path, params=parameters, bg_tasks=bg_tasks)
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job_id = transcription_job["job_id"]
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# Poll for completion
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@ -80,7 +80,8 @@ async def transcribe_endpoint(
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# If we've reached this point, the transcription has taken too long
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return JSONResponse(content={"status": "timeout", "message": "Transcription is taking longer than expected. Please check back later."}, status_code=202)
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async def transcribe_audio(file_path, params: TranscribeParams, background_tasks: BackgroundTasks):
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async def transcribe_audio(file_path, params: TranscribeParams, bg_tasks: BackgroundTasks):
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L.DEBUG(f"Transcribing audio file from {file_path}...")
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file_path = await convert_to_wav(file_path)
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model = params.model if params.model in WHISPER_CPP_MODELS else 'small'
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model_path = WHISPER_CPP_DIR / 'models' / f'ggml-{model}.bin'
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@ -117,7 +118,6 @@ async def transcribe_audio(file_path, params: TranscribeParams, background_tasks
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command.extend(['--dtw', params.dtw])
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command.extend(['-f', file_path])
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L.DEBUG(f"Command: {command}")
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# Create a unique ID for this transcription job
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@ -127,9 +127,21 @@ async def transcribe_audio(file_path, params: TranscribeParams, background_tasks
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transcription_results[job_id] = {"status": "processing", "result": None}
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# Run the transcription in a background task
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background_tasks.add_task(process_transcription, command, file_path, job_id)
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bg_tasks.add_task(process_transcription, command, file_path, job_id)
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return {"job_id": job_id}
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max_wait_time = 300 # 5 minutes
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poll_interval = 1 # 1 second
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start_time = asyncio.get_event_loop().time()
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while asyncio.get_event_loop().time() - start_time < max_wait_time:
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job_status = transcription_results.get(job_id, {})
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if job_status["status"] == "completed":
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return job_status["result"]
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elif job_status["status"] == "failed":
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raise Exception(f"Transcription failed: {job_status.get('error', 'Unknown error')}")
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await asyncio.sleep(poll_interval)
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raise TimeoutError("Transcription timed out")
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async def process_transcription(command, file_path, job_id):
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try:
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@ -522,7 +522,7 @@ async def summarize_post(file: Optional[UploadFile] = File(None), text: Optional
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return summarized_text
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@llm.post("/speaksummary")
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async def summarize_tts_endpoint(background_tasks: BackgroundTasks, instruction: str = Form(SUMMARY_INSTRUCT), file: Optional[UploadFile] = File(None), text: Optional[str] = Form(None), voice: Optional[str] = Form(DEFAULT_VOICE), speed: Optional[float] = Form(1.2), podcast: Union[bool, str] = Form(False)):
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async def summarize_tts_endpoint(bg_tasks: BackgroundTasks, instruction: str = Form(SUMMARY_INSTRUCT), file: Optional[UploadFile] = File(None), text: Optional[str] = Form(None), voice: Optional[str] = Form(DEFAULT_VOICE), speed: Optional[float] = Form(1.2), podcast: Union[bool, str] = Form(False)):
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podcast = str_to_bool(str(podcast)) # Proper boolean conversion
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text_content = text if text else extract_text(file)
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@ -546,8 +546,8 @@ async def summarize_tts(
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timestamp = dt_datetime.now().strftime("%Y%m%d_%H%M%S")
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filename = f"{timestamp}{filename}.wav"
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background_tasks = BackgroundTasks()
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final_output_path = await generate_speech(background_tasks, summarized_text, voice, "xtts", speed=speed, podcast=podcast, title=filename)
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bg_tasks = BackgroundTasks()
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final_output_path = await generate_speech(bg_tasks, summarized_text, voice, "xtts", speed=speed, podcast=podcast, title=filename)
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L.DEBUG(f"summary_tts completed with final_output_path: {final_output_path}")
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return final_output_path
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@ -578,7 +578,7 @@ def calculate_max_tokens(text: str) -> int:
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return min(tokens_count // 4, SUMMARY_CHUNK_SIZE)
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async def extract_text(file: Union[UploadFile, bytes, bytearray, str, Path], background_tasks: BackgroundTasks = None) -> str:
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async def extract_text(file: Union[UploadFile, bytes, bytearray, str, Path], bg_tasks: BackgroundTasks = None) -> str:
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if isinstance(file, UploadFile):
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file_extension = get_extension(file)
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temp_file_path = tempfile.mktemp(suffix=file_extension)
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@ -614,8 +614,8 @@ async def extract_text(file: Union[UploadFile, bytes, bytearray, str, Path], bac
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elif file_ext == '.docx':
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text_content = await extract_text_from_docx(file_path)
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if background_tasks and 'temp_file_path' in locals():
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background_tasks.add_task(os.remove, temp_file_path)
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if bg_tasks and 'temp_file_path' in locals():
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bg_tasks.add_task(os.remove, temp_file_path)
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elif 'temp_file_path' in locals():
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os.remove(temp_file_path)
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@ -14,6 +14,7 @@ import asyncio
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import pytz
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import aiohttp
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import folium
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from zoneinfo import ZoneInfo
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import time as timer
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from dateutil.parser import parse as dateutil_parse
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from concurrent.futures import ThreadPoolExecutor
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@ -158,20 +159,8 @@ async def geocode(zip_code: Optional[str] = None, latitude: Optional[float] = No
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async def localize_datetime(dt: Union[str, datetime], fetch_loc: bool = False) -> datetime:
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"""
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Localize a datetime object or string to the appropriate timezone.
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Args:
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dt (Union[str, datetime]): The datetime to localize.
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fetch_loc (bool): Whether to fetch the current location for timezone.
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Returns:
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datetime: A timezone-aware datetime object.
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Raises:
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ValueError: If the input cannot be parsed as a datetime.
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"""
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try:
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# Convert string to datetime if necessary
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if isinstance(dt, str):
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@ -181,14 +170,23 @@ async def localize_datetime(dt: Union[str, datetime], fetch_loc: bool = False) -
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if not isinstance(dt, datetime):
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raise ValueError("Input must be a string or datetime object.")
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# Fetch timezone
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# Fetch timezone string
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if fetch_loc:
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loc = await get_last_location()
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tz = await DynamicTZ.get_current(loc)
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L.DEBUG(f"Fetched current timezone: {tz}")
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tz_str = DynamicTZ.find(loc[0], loc[1]) # Assuming loc is (lat, lon)
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else:
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tz = await DynamicTZ.get_last()
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L.DEBUG(f"Using last known timezone: {tz}")
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tz_str = DynamicTZ.last_timezone
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L.DEBUG(f"Retrieved timezone string: {tz_str}")
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# Convert timezone string to ZoneInfo object
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try:
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tz = ZoneInfo(tz_str)
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except Exception as e:
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L.WARN(f"Invalid timezone string '{tz_str}'. Falling back to UTC. Error: {e}")
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tz = ZoneInfo('UTC')
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L.DEBUG(f"Using timezone: {tz}")
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# Localize datetime
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if dt.tzinfo is None:
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@ -199,7 +197,6 @@ async def localize_datetime(dt: Union[str, datetime], fetch_loc: bool = False) -
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L.DEBUG(f"Converted datetime from {dt.tzinfo} to {tz}")
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return dt
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except ValueError as e:
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L.ERR(f"Error parsing datetime: {e}")
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raise
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@ -208,7 +205,6 @@ async def localize_datetime(dt: Union[str, datetime], fetch_loc: bool = False) -
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raise ValueError(f"Failed to localize datetime: {e}")
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async def find_override_locations(lat: float, lon: float) -> Optional[str]:
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# Load the JSON file
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with open(NAMED_LOCATIONS, 'r') as file:
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@ -133,7 +133,7 @@ async def build_daily_timeslips(date):
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### CLIPPER ###
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@note.post("/clip")
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async def clip_post(
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background_tasks: BackgroundTasks,
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bg_tasks: BackgroundTasks,
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file: UploadFile = None,
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url: Optional[str] = Form(None),
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source: Optional[str] = Form(None),
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@ -142,65 +142,64 @@ async def clip_post(
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voice: str = Form(DEFAULT_VOICE),
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encoding: str = Form('utf-8')
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):
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markdown_filename = await process_article(background_tasks, url, title, encoding, source, tts, voice)
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markdown_filename = await process_article(bg_tasks, url, title, encoding, source, tts, voice)
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return {"message": "Clip saved successfully", "markdown_filename": markdown_filename}
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@note.post("/archive")
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async def archive_post(
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background_tasks: BackgroundTasks,
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bg_tasks: BackgroundTasks,
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file: UploadFile = None,
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url: Optional[str] = Form(None),
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source: Optional[str] = Form(None),
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title: Optional[str] = Form(None),
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encoding: str = Form('utf-8')
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):
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markdown_filename = await process_archive(background_tasks, url, title, encoding, source)
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markdown_filename = await process_archive(bg_tasks, url, title, encoding, source)
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return {"message": "Clip saved successfully", "markdown_filename": markdown_filename}
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@note.get("/clip")
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async def clip_get(
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background_tasks: BackgroundTasks,
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bg_tasks: BackgroundTasks,
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url: str,
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title: Optional[str] = Query(None),
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encoding: str = Query('utf-8'),
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tts: str = Query('summary'),
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voice: str = Query(DEFAULT_VOICE)
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):
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markdown_filename = await process_article(background_tasks, url, title, encoding, tts=tts, voice=voice)
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markdown_filename = await process_article(bg_tasks, url, title, encoding, tts=tts, voice=voice)
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return {"message": "Clip saved successfully", "markdown_filename": markdown_filename}
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@note.post("/note/add")
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async def note_add_endpoint(file: Optional[UploadFile] = File(None), text: Optional[str] = Form(None), source: Optional[str] = Form(None)):
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async def note_add_endpoint(file: Optional[UploadFile] = File(None), text: Optional[str] = Form(None), source: Optional[str] = Form(None), bg_tasks: BackgroundTasks = None):
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L.DEBUG(f"Received request on /note/add...")
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if not file and not text:
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L.WARN(f"... without any file or text!")
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raise HTTPException(status_code=400, detail="Either text or a file must be provided")
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else:
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result = await process_for_daily_note(file, text, source)
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result = await process_for_daily_note(file, text, source, bg_tasks)
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L.INFO(f"Result on /note/add: {result}")
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return JSONResponse(result, status_code=204)
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async def process_for_daily_note(file: Optional[UploadFile] = File(None), text: Optional[str] = None, source: Optional[str] = None):
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async def process_for_daily_note(file: Optional[UploadFile] = File(None), text: Optional[str] = None, source: Optional[str] = None, bg_tasks: BackgroundTasks = None):
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now = datetime.now()
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transcription_entry = ""
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file_entry = ""
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if file:
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L.DEBUG("File received...")
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file_content = await file.read()
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audio_io = BytesIO(file_content)
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file_type, _ = mimetypes.guess_type(file.filename)
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if 'audio' in file_type:
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subdir = "Audio"
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elif 'image' in file_type:
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subdir = "Images"
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else:
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subdir = "Documents"
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L.DEBUG(f"Processing as {file_type}...")
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subdir = file_type.title() or "Documents"
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absolute_path, relative_path = assemble_journal_path(now, subdir=subdir, filename=file.filename)
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L.DEBUG(f"Destination path: {absolute_path}")
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with open(absolute_path, 'wb') as f:
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f.write(file_content)
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L.DEBUG(f"Processing {f.name}...")
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if 'audio' in file_type:
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transcription = await asr.transcribe_audio(file_path=absolute_path, params=asr.TranscribeParams(model="small-en", language="en", threads=6))
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transcription = await asr.transcribe_audio(file_path=absolute_path, params=asr.TranscribeParams(model="small-en", language="en", threads=6), bg_tasks=bg_tasks)
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file_entry = f"![[{relative_path}]]"
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elif 'image' in file_type:
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@ -209,7 +208,6 @@ async def process_for_daily_note(file: Optional[UploadFile] = File(None), text:
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else:
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file_entry = f"[Source]({relative_path})"
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text_entry = text if text else ""
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L.DEBUG(f"transcription: {transcription}\nfile_entry: {file_entry}\ntext_entry: {text_entry}")
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return await add_to_daily_note(transcription, file_entry, text_entry, now)
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@ -262,7 +260,7 @@ async def handle_text(title:str, summary:str, extracted_text:str, date_time: dat
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async def process_document(
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background_tasks: BackgroundTasks,
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bg_tasks: BackgroundTasks,
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document: File,
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title: Optional[str] = None,
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tts_mode: str = "summary",
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@ -301,7 +299,7 @@ added: {timestamp}
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datetime_str = datetime.now().strftime("%Y%m%d%H%M%S")
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audio_filename = f"{datetime_str} {readable_title}"
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audio_path = await tts.generate_speech(
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background_tasks=background_tasks,
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bg_tasks=bg_tasks,
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text=tts_text,
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voice=voice,
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model="eleven_turbo_v2",
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@ -336,7 +334,7 @@ added: {timestamp}
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async def process_article(
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background_tasks: BackgroundTasks,
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bg_tasks: BackgroundTasks,
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url: str,
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title: Optional[str] = None,
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encoding: str = 'utf-8',
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@ -397,7 +395,7 @@ tags:
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datetime_str = datetime.now().strftime("%Y%m%d%H%M%S")
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audio_filename = f"{datetime_str} {readable_title}"
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try:
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audio_path = await tts.generate_speech(background_tasks=background_tasks, text=tts_text, voice=voice, model="eleven_turbo_v2", podcast=True, title=audio_filename,
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audio_path = await tts.generate_speech(bg_tasks=bg_tasks, text=tts_text, voice=voice, model="eleven_turbo_v2", podcast=True, title=audio_filename,
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output_dir=Path(OBSIDIAN_VAULT_DIR) / OBSIDIAN_RESOURCES_DIR)
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audio_ext = Path(audio_path).suffix
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obsidian_link = f"![[{OBSIDIAN_RESOURCES_DIR}/{audio_filename}{audio_ext}]]"
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@ -502,7 +500,7 @@ async def html_to_markdown(url: str = None, source: str = None) -> Optional[str]
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async def process_archive(
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background_tasks: BackgroundTasks,
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bg_tasks: BackgroundTasks,
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url: str,
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title: Optional[str] = None,
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encoding: str = 'utf-8',
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@ -136,7 +136,7 @@ async def hook_changedetection(webhook_data: dict):
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@serve.post("/cl/search")
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async def hook_cl_search(request: Request, background_tasks: BackgroundTasks):
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async def hook_cl_search(request: Request, bg_tasks: BackgroundTasks):
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client_ip = request.client.host
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L.DEBUG(f"Received request from IP: {client_ip}")
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data = await request.json()
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@ -150,7 +150,7 @@ async def hook_cl_search(request: Request, background_tasks: BackgroundTasks):
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json.dump(payload, file, indent=2)
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for result in results:
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background_tasks.add_task(cl_search_process_result, result)
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bg_tasks.add_task(cl_search_process_result, result)
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return JSONResponse(content={"message": "Received"}, status_code=status.HTTP_200_OK)
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@serve.post("/cl/docket")
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@ -283,7 +283,7 @@ def shellfish_run_widget_command(args: List[str]):
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### COURTLISTENER FUNCTIONS ###
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async def cl_docket(data, client_ip, background_tasks: BackgroundTasks):
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async def cl_docket(data, client_ip, bg_tasks: BackgroundTasks):
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payload = data['payload']
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results = data['payload']['results']
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timestamp = datetime.now().strftime("%Y%m%d-%H%M%S")
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@ -292,7 +292,7 @@ async def cl_docket(data, client_ip, background_tasks: BackgroundTasks):
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json.dump(payload, file, indent=2)
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for result in results:
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background_tasks.add_task(cl_docket_process, result)
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bg_tasks.add_task(cl_docket_process, result)
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return JSONResponse(content={"message": "Received"}, status_code=status.HTTP_200_OK)
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async def cl_docket_process(result):
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@ -87,7 +87,7 @@ def select_voice(voice_name: str) -> str:
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@tts.post("/v1/audio/speech")
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async def generate_speech_endpoint(
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request: Request,
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background_tasks: BackgroundTasks,
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bg_tasks: BackgroundTasks,
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model: str = Form("eleven_turbo_v2"),
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text: Optional[str] = Form(None),
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file: Optional[UploadFile] = File(None),
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@ -110,7 +110,7 @@ async def generate_speech_endpoint(
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else:
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return await stream_tts(text_content, speed, voice, voice_file)
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else:
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return await generate_speech(background_tasks, text_content, voice, voice_file, model, speed, podcast)
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return await generate_speech(bg_tasks, text_content, voice, voice_file, model, speed, podcast)
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except Exception as e:
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L.ERR(f"Error in TTS: {str(e)}")
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L.ERR(traceback.format_exc())
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@ -118,7 +118,7 @@ async def generate_speech_endpoint(
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async def generate_speech(
|
||||
background_tasks: BackgroundTasks,
|
||||
bg_tasks: BackgroundTasks,
|
||||
text: str,
|
||||
voice: str = None,
|
||||
voice_file: UploadFile = None,
|
||||
|
|
@ -142,8 +142,8 @@ async def generate_speech(
|
|||
|
||||
elif model == "xtts":
|
||||
L.INFO(f"Using XTTS2")
|
||||
final_output_dir = await local_tts(text, speed, voice, voice_file, podcast, background_tasks, title, output_dir)
|
||||
background_tasks.add_task(os.remove, str(final_output_dir))
|
||||
final_output_dir = await local_tts(text, speed, voice, voice_file, podcast, bg_tasks, title, output_dir)
|
||||
bg_tasks.add_task(os.remove, str(final_output_dir))
|
||||
return str(final_output_dir)
|
||||
else:
|
||||
raise HTTPException(status_code=400, detail="Invalid model specified")
|
||||
|
|
@ -282,7 +282,7 @@ async def local_tts(
|
|||
voice: str,
|
||||
voice_file = None,
|
||||
podcast: bool = False,
|
||||
background_tasks: BackgroundTasks = None,
|
||||
bg_tasks: BackgroundTasks = None,
|
||||
title: str = None,
|
||||
output_path: Optional[Path] = None
|
||||
) -> str:
|
||||
|
|
|
|||
Loading…
Reference in a new issue