public-mirrors/Kokoro-FastAPI
1
0
Fork 0
mirror of https://github.com/remsky/Kokoro-FastAPI.git synced 2025-08-05 16:48:53 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

fixed no stream file writing

Browse source
This commit is contained in:
Fireblade 2025-02-13 16:12:51 -05:00
parent dbf2b99026
commit 7772dbc2e4
4 changed files with 28 additions and 28 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

2
api/src/inference/base.py
View file

@ -21,7 +21,7 @@ class AudioChunk:
output=AudioChunk(audio_chunk_list[0].audio,audio_chunk_list[0].word_timestamps)
for audio_chunk in audio_chunk_list[1:]:
output.audio=np.concatenate((output.audio,audio_chunk.audio))
output.audio=np.concatenate((output.audio,audio_chunk.audio),dtype=np.int16)
if output.word_timestamps is not None:
output.word_timestamps+=output.word_timestamps

18
api/src/routers/openai_compatible.py
View file

@ -7,6 +7,7 @@ import re
import tempfile
from typing import AsyncGenerator, Dict, List, Union, Tuple
from urllib import response
import numpy as np
import aiofiles
from ..inference.base import AudioChunk
@ -259,24 +260,31 @@ async def create_speech(
)
else:
# Generate complete audio using public interface
audio, audio_data = await tts_service.generate_audio(
_, audio_data = await tts_service.generate_audio(
text=request.input,
voice=voice_name,
speed=request.speed,
lang_code=request.lang_code,
)
# Convert to requested format with proper finalization
content, audio_data = await AudioService.convert_audio(
audio_data,
24000,
request.response_format,
is_first_chunk=True,
is_last_chunk=False,
)
# Convert to requested format with proper finalization
final, _ = await AudioService.convert_audio(
AudioChunk(np.array([], dtype=np.int16)),
24000,
request.response_format,
is_first_chunk=False,
is_last_chunk=True,
)
print(content,request.response_format)
output=content+final
return Response(
content=content,
content=output,
media_type=content_type,
headers={
"Content-Disposition": f"attachment; filename=speech.{request.response_format}",

20
api/src/services/audio.py
View file

@ -72,7 +72,7 @@ class AudioNormalizer:
return max(non_silent_index_start - self.samples_to_pad_start,0), min(non_silent_index_end + math.ceil(samples_to_pad_end / speed),len(audio_data))
async def normalize(self, audio_data: np.ndarray) -> np.ndarray:
def normalize(self, audio_data: np.ndarray) -> np.ndarray:
"""Convert audio data to int16 range
Args:
@ -80,12 +80,10 @@ class AudioNormalizer:
Returns:
Normalized audio data
"""
if len(audio_data) == 0:
raise ValueError("Empty audio data")
# Scale directly to int16 range with clipping
return np.clip(audio_data * 32767, -32768, 32767).astype(np.int16)
if audio_data.dtype != np.int16:
# Scale directly to int16 range with clipping
return np.clip(audio_data * 32767, -32768, 32767).astype(np.int16)
return audio_data
class AudioService:
"""Service for audio format conversions with streaming support"""
@ -148,11 +146,9 @@ class AudioService:
if normalizer is None:
normalizer = AudioNormalizer()
print(len(audio_chunk.audio),"1")
audio_chunk.audio = await normalizer.normalize(audio_chunk.audio)
print(len(audio_chunk.audio),"2")
audio_chunk.audio = normalizer.normalize(audio_chunk.audio)
audio_chunk = AudioService.trim_audio(audio_chunk,chunk_text,speed,is_last_chunk,normalizer)
print(len(audio_chunk.audio),"3")
# Get or create format-specific writer
writer_key = f"{output_format}_{sample_rate}"
if is_first_chunk or writer_key not in AudioService._writers:
@ -169,7 +165,6 @@ class AudioService:
if is_last_chunk:
final_data = writer.write_chunk(finalize=True)
del AudioService._writers[writer_key]
print(audio_chunk.audio)
return final_data if final_data else b"", audio_chunk
return chunk_data if chunk_data else b"", audio_chunk
@ -196,6 +191,7 @@ class AudioService:
if normalizer is None:
normalizer = AudioNormalizer()
audio_chunk.audio=normalizer.normalize(audio_chunk.audio)
# Trim start and end if enough samples
if len(audio_chunk.audio) > (2 * normalizer.samples_to_trim):
audio_chunk.audio = audio_chunk.audio[normalizer.samples_to_trim : -normalizer.samples_to_trim]

16
api/src/services/tts_service.py
View file

@ -62,7 +62,7 @@ class TTSService:
if is_last:
# Skip format conversion for raw audio mode
if not output_format:
yield np.array([], dtype=np.float32)
yield np.array([], dtype=np.int16), AudioChunk(np.array([], dtype=np.int16))
return
result, chunk_data = await AudioService.convert_audio(
AudioChunk(np.array([0], dtype=np.float32)), # Dummy data for type checking
@ -111,7 +111,7 @@ class TTSService:
except Exception as e:
logger.error(f"Failed to convert audio: {str(e)}")
else:
chunk_data = await AudioService.trim_audio(chunk_data,
chunk_data = AudioService.trim_audio(chunk_data,
chunk_text,
speed,
is_last,
@ -152,7 +152,7 @@ class TTSService:
except Exception as e:
logger.error(f"Failed to convert audio: {str(e)}")
else:
trimmed = await AudioService.trim_audio(chunk_data,
trimmed = AudioService.trim_audio(chunk_data,
chunk_text,
speed,
is_last,
@ -288,7 +288,6 @@ class TTSService:
current_offset+=len(chunk_data.audio) / 24000
if result is not None:
print(chunk_data.word_timestamps)
yield result,chunk_data
chunk_index += 1
else:
@ -342,17 +341,14 @@ class TTSService:
audio_data_chunks=[]
try:
async for audio_stream,audio_stream_data in self.generate_audio_stream(text,voice,speed=speed,return_timestamps=return_timestamps,lang_code=lang_code):
async for audio_stream,audio_stream_data in self.generate_audio_stream(text,voice,speed=speed,return_timestamps=return_timestamps,lang_code=lang_code,output_format=None):
audio_chunks.append(audio_stream_data.audio)
audio_data_chunks.append(audio_stream_data)
print(audio_data_chunks[0].audio.shape)
combined_audio=np.concatenate(audio_chunks)
print("1")
combined_audio=np.concatenate(audio_chunks,dtype=np.int16)
combined_audio_data=AudioChunk.combine(audio_data_chunks)
print("2")
print(len(combined_audio_data.audio))
return combined_audio,combined_audio_data
"""
# Get backend and voice path