update with up to date example

README.md

@@ -142,52 +142,79 @@ whisperlivekit-server --host 0.0.0.0 --port 8000 --model medium --diarization --
 ```
 
 ### Python API Integration (Backend)
+Check [basic_server.py](https://github.com/QuentinFuxa/WhisperLiveKit/blob/main/whisperlivekit/basic_server.py) for a complete example.
 
 ```python
-from whisperlivekit import WhisperLiveKit
-from whisperlivekit.audio_processor import AudioProcessor
-from fastapi import FastAPI, WebSocket
-import asyncio
+from whisperlivekit import TranscriptionEngine, AudioProcessor, get_web_interface_html, parse_args
+from fastapi import FastAPI, WebSocket, WebSocketDisconnect
 from fastapi.responses import HTMLResponse
+from contextlib import asynccontextmanager
+import asyncio
 
-# Initialize components
-app = FastAPI()
-kit = WhisperLiveKit(model="medium", diarization=True)
+# Global variable for the transcription engine
+transcription_engine = None
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    global transcription_engine
+    # Example: Initialize with specific parameters directly
+    # You can also load from command-line arguments using parse_args()
+    # args = parse_args()
+    # transcription_engine = TranscriptionEngine(**vars(args))
+    transcription_engine = TranscriptionEngine(model="medium", diarization=True, lan="en")
+    yield
+
+app = FastAPI(lifespan=lifespan)
 
 # Serve the web interface
 @app.get("/")
 async def get():
-    return HTMLResponse(kit.web_interface())  # Use the built-in web interface
+    return HTMLResponse(get_web_interface_html())
 
 # Process WebSocket connections
-async def handle_websocket_results(websocket, results_generator):
-    async for response in results_generator:
-        await websocket.send_json(response)
+async def handle_websocket_results(websocket: WebSocket, results_generator):
+    try:
+        async for response in results_generator:
+            await websocket.send_json(response)
+        await websocket.send_json({"type": "ready_to_stop"})
+    except WebSocketDisconnect:
+        print("WebSocket disconnected during results handling.")
 
 @app.websocket("/asr")
 async def websocket_endpoint(websocket: WebSocket):
-    audio_processor = AudioProcessor()
-    await websocket.accept()
-    results_generator = await audio_processor.create_tasks()
-    websocket_task = asyncio.create_task(
-        handle_websocket_results(websocket, results_generator)
-    )
+    global transcription_engine
 
+    # Create a new AudioProcessor for each connection, passing the shared engine
+    audio_processor = AudioProcessor(transcription_engine=transcription_engine)    
+    results_generator = await audio_processor.create_tasks()
+    send_results_to_client = handle_websocket_results(websocket, results_generator)
+    results_task = asyncio.create_task(send_results_to_client)
+    await websocket.accept()
     try:
         while True:
             message = await websocket.receive_bytes()
-            await audio_processor.process_audio(message)
+            await audio_processor.process_audio(message)        
+    except WebSocketDisconnect:
+        print(f"Client disconnected: {websocket.client}")
     except Exception as e:
-        print(f"WebSocket error: {e}")
-        websocket_task.cancel()
+        await websocket.close(code=1011, reason=f"Server error: {e}")
+    finally:
+        results_task.cancel()
+        try:
+            await results_task
+        except asyncio.CancelledError:
+            logger.info("Results task successfully cancelled.")
 ```
 
 ### Frontend Implementation
 
-The package includes a simple HTML/JavaScript implementation that you can adapt for your project. You can get in in [whisperlivekit/web/live_transcription.html](https://github.com/QuentinFuxa/WhisperLiveKit/blob/main/whisperlivekit/web/live_transcription.html), or using :
+The package includes a simple HTML/JavaScript implementation that you can adapt for your project. You can find it in `whisperlivekit/web/live_transcription.html`, or load its content using the `get_web_interface_html()` function from `whisperlivekit`:
 
 ```python
-kit.web_interface()
+from whisperlivekit import get_web_interface_html
+
+# ... later in your code where you need the HTML string ...
+html_content = get_web_interface_html()
 ```
 
 ## ⚙️ Configuration Reference

setup.py

@@ -1,7 +1,7 @@
 from setuptools import setup, find_packages
 setup(
     name="whisperlivekit",
-    version="0.1.7",
+    version="0.1.8",
     description="Real-time, Fully Local Whisper's Speech-to-Text and Speaker Diarization",
     long_description=open("README.md", "r", encoding="utf-8").read(),
     long_description_content_type="text/markdown",

whisperlivekit/__init__.py

@@ -1,4 +1,5 @@
-from .core import WhisperLiveKit, parse_args
+from .core import TranscriptionEngine
 from .audio_processor import AudioProcessor
-
-__all__ = ['WhisperLiveKit', 'AudioProcessor', 'parse_args']
+from .web.web_interface import get_web_interface_html
+from .parse_args import parse_args
+__all__ = ['TranscriptionEngine', 'AudioProcessor', 'get_web_interface_html', 'parse_args']

whisperlivekit/audio_processor.py

@@ -8,7 +8,7 @@ import traceback
 from datetime import timedelta
 from whisperlivekit.timed_objects import ASRToken
 from whisperlivekit.whisper_streaming_custom.whisper_online import online_factory
-from whisperlivekit.core import WhisperLiveKit
+from whisperlivekit.core import TranscriptionEngine
 
 # Set up logging once
 logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
@@ -27,10 +27,13 @@ class AudioProcessor:
     Handles audio processing, state management, and result formatting.
     """
     
-    def __init__(self):
+    def __init__(self, **kwargs):
         """Initialize the audio processor with configuration, models, and state."""
         
-        models = WhisperLiveKit()
+        if 'transcription_engine' in kwargs and isinstance(kwargs['transcription_engine'], TranscriptionEngine):
+            models = kwargs['transcription_engine']
+        else:
+            models = TranscriptionEngine(**kwargs)
         
         # Audio processing settings
         self.args = models.args

whisperlivekit/basic_server.py

@@ -2,26 +2,24 @@ from contextlib import asynccontextmanager
 from fastapi import FastAPI, WebSocket, WebSocketDisconnect
 from fastapi.responses import HTMLResponse
 from fastapi.middleware.cors import CORSMiddleware
-
-from whisperlivekit import WhisperLiveKit, parse_args
-from whisperlivekit.audio_processor import AudioProcessor
-
+from whisperlivekit import TranscriptionEngine, AudioProcessor, get_web_interface_html, parse_args
 import asyncio
 import logging
-import os, sys
-import argparse
 
 logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
 logging.getLogger().setLevel(logging.WARNING)
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.DEBUG)
 
-kit = None
+args = parse_args()
+transcription_engine = None
 
 @asynccontextmanager
 async def lifespan(app: FastAPI):
-    global kit
-    kit = WhisperLiveKit()
+    global transcription_engine
+    transcription_engine = TranscriptionEngine(
+        **vars(args),
+    )
     yield
 
 app = FastAPI(lifespan=lifespan)
@@ -33,10 +31,9 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-
 @app.get("/")
 async def get():
-    return HTMLResponse(kit.web_interface())
+    return HTMLResponse(get_web_interface_html())
 
 
 async def handle_websocket_results(websocket, results_generator):
@@ -55,8 +52,10 @@ async def handle_websocket_results(websocket, results_generator):
 
 @app.websocket("/asr")
 async def websocket_endpoint(websocket: WebSocket):
-    audio_processor = AudioProcessor()
-
+    global transcription_engine
+    audio_processor = AudioProcessor(
+        transcription_engine=transcription_engine,
+    )
     await websocket.accept()
     logger.info("WebSocket connection opened.")
             
@@ -94,8 +93,6 @@ def main():
     """Entry point for the CLI command."""
     import uvicorn
     
-    args = parse_args()
-    
     uvicorn_kwargs = {
         "app": "whisperlivekit.basic_server:app",
         "host":args.host, 
@@ -114,7 +111,6 @@ def main():
             "ssl_keyfile": args.ssl_keyfile
         }
 
-
     if ssl_kwargs:
         uvicorn_kwargs = {**uvicorn_kwargs, **ssl_kwargs}
 

whisperlivekit/core.py

@@ -2,148 +2,10 @@ try:
     from whisperlivekit.whisper_streaming_custom.whisper_online import backend_factory, warmup_asr
 except ImportError:
     from .whisper_streaming_custom.whisper_online import backend_factory, warmup_asr
-from argparse import Namespace, ArgumentParser
-
-def parse_args():
-    parser = ArgumentParser(description="Whisper FastAPI Online Server")
-    parser.add_argument(
-        "--host",
-        type=str,
-        default="localhost",
-        help="The host address to bind the server to.",
-    )
-    parser.add_argument(
-        "--port", type=int, default=8000, help="The port number to bind the server to."
-    )
-    parser.add_argument(
-        "--warmup-file",
-        type=str,
-        default=None,
-        dest="warmup_file",
-        help="""
-        The path to a speech audio wav file to warm up Whisper so that the very first chunk processing is fast.
-        If not set, uses https://github.com/ggerganov/whisper.cpp/raw/master/samples/jfk.wav.
-        If False, no warmup is performed.
-        """,
-    )
-
-    parser.add_argument(
-        "--confidence-validation",
-        action="store_true",
-        help="Accelerates validation of tokens using confidence scores. Transcription will be faster but punctuation might be less accurate.",
-    )
-
-    parser.add_argument(
-        "--diarization",
-        action="store_true",
-        default=False,
-        help="Enable speaker diarization.",
-    )
-
-    parser.add_argument(
-        "--no-transcription",
-        action="store_true",
-        help="Disable transcription to only see live diarization results.",
-    )
-    
-    parser.add_argument(
-        "--min-chunk-size",
-        type=float,
-        default=0.5,
-        help="Minimum audio chunk size in seconds. It waits up to this time to do processing. If the processing takes shorter time, it waits, otherwise it processes the whole segment that was received by this time.",
-    )
-    
-    parser.add_argument(
-        "--model",
-        type=str,
-        default="tiny",
-        help="Name size of the Whisper model to use (default: tiny). Suggested values: tiny.en,tiny,base.en,base,small.en,small,medium.en,medium,large-v1,large-v2,large-v3,large,large-v3-turbo. The model is automatically downloaded from the model hub if not present in model cache dir.",
-    )
-    
-    parser.add_argument(
-        "--model_cache_dir",
-        type=str,
-        default=None,
-        help="Overriding the default model cache dir where models downloaded from the hub are saved",
-    )
-    parser.add_argument(
-        "--model_dir",
-        type=str,
-        default=None,
-        help="Dir where Whisper model.bin and other files are saved. This option overrides --model and --model_cache_dir parameter.",
-    )
-    parser.add_argument(
-        "--lan",
-        "--language",
-        type=str,
-        default="auto",
-        help="Source language code, e.g. en,de,cs, or 'auto' for language detection.",
-    )
-    parser.add_argument(
-        "--task",
-        type=str,
-        default="transcribe",
-        choices=["transcribe", "translate"],
-        help="Transcribe or translate.",
-    )
-    parser.add_argument(
-        "--backend",
-        type=str,
-        default="faster-whisper",
-        choices=["faster-whisper", "whisper_timestamped", "mlx-whisper", "openai-api"],
-        help="Load only this backend for Whisper processing.",
-    )
-    parser.add_argument(
-        "--vac",
-        action="store_true",
-        default=False,
-        help="Use VAC = voice activity controller. Recommended. Requires torch.",
-    )
-    parser.add_argument(
-        "--vac-chunk-size", type=float, default=0.04, help="VAC sample size in seconds."
-    )
-
-    parser.add_argument(
-        "--no-vad",
-        action="store_true",
-        help="Disable VAD (voice activity detection).",
-    )
-    
-    parser.add_argument(
-        "--buffer_trimming",
-        type=str,
-        default="segment",
-        choices=["sentence", "segment"],
-        help='Buffer trimming strategy -- trim completed sentences marked with punctuation mark and detected by sentence segmenter, or the completed segments returned by Whisper. Sentence segmenter must be installed for "sentence" option.',
-    )
-    parser.add_argument(
-        "--buffer_trimming_sec",
-        type=float,
-        default=15,
-        help="Buffer trimming length threshold in seconds. If buffer length is longer, trimming sentence/segment is triggered.",
-    )
-    parser.add_argument(
-        "-l",
-        "--log-level",
-        dest="log_level",
-        choices=["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"],
-        help="Set the log level",
-        default="DEBUG",
-    )
-    parser.add_argument("--ssl-certfile", type=str, help="Path to the SSL certificate file.", default=None)
-    parser.add_argument("--ssl-keyfile", type=str, help="Path to the SSL private key file.", default=None)
+from argparse import Namespace
 
 
-    args = parser.parse_args()
-    
-    args.transcription = not args.no_transcription
-    args.vad = not args.no_vad    
-    delattr(args, 'no_transcription')
-    delattr(args, 'no_vad')
-    
-    return args
-
-class WhisperLiveKit:
+class TranscriptionEngine:
     _instance = None
     _initialized = False
     
@@ -153,14 +15,48 @@ class WhisperLiveKit:
         return cls._instance
     
     def __init__(self, **kwargs):
-        if WhisperLiveKit._initialized:
+        if TranscriptionEngine._initialized:
             return
-            
-        default_args = vars(parse_args())
+
+        defaults = {
+            "host": "localhost",
+            "port": 8000,
+            "warmup_file": None,
+            "confidence_validation": False,
+            "diarization": False,
+            "min_chunk_size": 0.5,
+            "model": "tiny",
+            "model_cache_dir": None,
+            "model_dir": None,
+            "lan": "auto",
+            "task": "transcribe",
+            "backend": "faster-whisper",
+            "vac": False,
+            "vac_chunk_size": 0.04,
+            "buffer_trimming": "segment",
+            "buffer_trimming_sec": 15,
+            "log_level": "DEBUG",
+            "ssl_certfile": None,
+            "ssl_keyfile": None,
+            "transcription": True, 
+            "vad": True,
+        }
+
+        config_dict = {**defaults, **kwargs}
+
+        if 'no_transcription' in kwargs:
+            config_dict['transcription'] = not kwargs['no_transcription']
+        if 'no_vad' in kwargs:
+            config_dict['vad'] = not kwargs['no_vad']
         
-        merged_args = {**default_args, **kwargs}
-        
-        self.args = Namespace(**merged_args)
+        config_dict.pop('no_transcription', None)
+        config_dict.pop('no_vad', None)
+
+        if 'language' in kwargs:
+            config_dict['lan'] = kwargs['language']
+        config_dict.pop('language', None) 
+
+        self.args = Namespace(**config_dict)
         
         self.asr = None
         self.tokenizer = None
@@ -174,11 +70,4 @@ class WhisperLiveKit:
             from whisperlivekit.diarization.diarization_online import DiartDiarization
             self.diarization = DiartDiarization()
             
-        WhisperLiveKit._initialized = True
-
-    def web_interface(self):
-        import pkg_resources
-        html_path = pkg_resources.resource_filename('whisperlivekit', 'web/live_transcription.html')
-        with open(html_path, "r", encoding="utf-8") as f:
-            html = f.read()
-        return html
+        TranscriptionEngine._initialized = True

whisperlivekit/parse_args.py

@@ -0,0 +1,141 @@
+
+from argparse import ArgumentParser
+
+def parse_args():
+    parser = ArgumentParser(description="Whisper FastAPI Online Server")
+    parser.add_argument(
+        "--host",
+        type=str,
+        default="localhost",
+        help="The host address to bind the server to.",
+    )
+    parser.add_argument(
+        "--port", type=int, default=8000, help="The port number to bind the server to."
+    )
+    parser.add_argument(
+        "--warmup-file",
+        type=str,
+        default=None,
+        dest="warmup_file",
+        help="""
+        The path to a speech audio wav file to warm up Whisper so that the very first chunk processing is fast.
+        If not set, uses https://github.com/ggerganov/whisper.cpp/raw/master/samples/jfk.wav.
+        If False, no warmup is performed.
+        """,
+    )
+
+    parser.add_argument(
+        "--confidence-validation",
+        action="store_true",
+        help="Accelerates validation of tokens using confidence scores. Transcription will be faster but punctuation might be less accurate.",
+    )
+
+    parser.add_argument(
+        "--diarization",
+        action="store_true",
+        default=False,
+        help="Enable speaker diarization.",
+    )
+
+    parser.add_argument(
+        "--no-transcription",
+        action="store_true",
+        help="Disable transcription to only see live diarization results.",
+    )
+    
+    parser.add_argument(
+        "--min-chunk-size",
+        type=float,
+        default=0.5,
+        help="Minimum audio chunk size in seconds. It waits up to this time to do processing. If the processing takes shorter time, it waits, otherwise it processes the whole segment that was received by this time.",
+    )
+    
+    parser.add_argument(
+        "--model",
+        type=str,
+        default="tiny",
+        help="Name size of the Whisper model to use (default: tiny). Suggested values: tiny.en,tiny,base.en,base,small.en,small,medium.en,medium,large-v1,large-v2,large-v3,large,large-v3-turbo. The model is automatically downloaded from the model hub if not present in model cache dir.",
+    )
+    
+    parser.add_argument(
+        "--model_cache_dir",
+        type=str,
+        default=None,
+        help="Overriding the default model cache dir where models downloaded from the hub are saved",
+    )
+    parser.add_argument(
+        "--model_dir",
+        type=str,
+        default=None,
+        help="Dir where Whisper model.bin and other files are saved. This option overrides --model and --model_cache_dir parameter.",
+    )
+    parser.add_argument(
+        "--lan",
+        "--language",
+        type=str,
+        default="auto",
+        help="Source language code, e.g. en,de,cs, or 'auto' for language detection.",
+    )
+    parser.add_argument(
+        "--task",
+        type=str,
+        default="transcribe",
+        choices=["transcribe", "translate"],
+        help="Transcribe or translate.",
+    )
+    parser.add_argument(
+        "--backend",
+        type=str,
+        default="faster-whisper",
+        choices=["faster-whisper", "whisper_timestamped", "mlx-whisper", "openai-api"],
+        help="Load only this backend for Whisper processing.",
+    )
+    parser.add_argument(
+        "--vac",
+        action="store_true",
+        default=False,
+        help="Use VAC = voice activity controller. Recommended. Requires torch.",
+    )
+    parser.add_argument(
+        "--vac-chunk-size", type=float, default=0.04, help="VAC sample size in seconds."
+    )
+
+    parser.add_argument(
+        "--no-vad",
+        action="store_true",
+        help="Disable VAD (voice activity detection).",
+    )
+    
+    parser.add_argument(
+        "--buffer_trimming",
+        type=str,
+        default="segment",
+        choices=["sentence", "segment"],
+        help='Buffer trimming strategy -- trim completed sentences marked with punctuation mark and detected by sentence segmenter, or the completed segments returned by Whisper. Sentence segmenter must be installed for "sentence" option.',
+    )
+    parser.add_argument(
+        "--buffer_trimming_sec",
+        type=float,
+        default=15,
+        help="Buffer trimming length threshold in seconds. If buffer length is longer, trimming sentence/segment is triggered.",
+    )
+    parser.add_argument(
+        "-l",
+        "--log-level",
+        dest="log_level",
+        choices=["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"],
+        help="Set the log level",
+        default="DEBUG",
+    )
+    parser.add_argument("--ssl-certfile", type=str, help="Path to the SSL certificate file.", default=None)
+    parser.add_argument("--ssl-keyfile", type=str, help="Path to the SSL private key file.", default=None)
+
+
+    args = parser.parse_args()
+    
+    args.transcription = not args.no_transcription
+    args.vad = not args.no_vad    
+    delattr(args, 'no_transcription')
+    delattr(args, 'no_vad')
+    
+    return args

whisperlivekit/web/web_interface.py

@@ -0,0 +1,13 @@
+import logging
+import importlib.resources as resources
+
+logger = logging.getLogger(__name__)
+
+def get_web_interface_html():
+    """Loads the HTML for the web interface using importlib.resources."""
+    try:
+        with resources.files('whisperlivekit.web').joinpath('live_transcription.html').open('r', encoding='utf-8') as f:
+            return f.read()
+    except Exception as e:
+        logger.error(f"Error loading web interface HTML: {e}")
+        return "<html><body><h1>Error loading interface</h1></body></html>"