public-mirrors/Kokoro-FastAPI
1
0
Fork 0
mirror of https://github.com/remsky/Kokoro-FastAPI.git synced 2025-04-13 09:39:17 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

Mostly completed work on refractoring a bunch of code as well as streaming word level time stamps

Browse source
This commit is contained in:
Fireblade 2025-02-14 14:29:47 -05:00
parent 0b5ec320c7
commit 34acb17682
7 changed files with 87 additions and 84 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

62
README.md
View file

@ -367,9 +367,10 @@ The model is capable of processing up to a 510 phonemized token chunk at a time,
<details>
<summary>Timestamped Captions & Phonemes</summary>
Generate audio with word-level timestamps:
Generate audio with word-level timestamps without streaming:
```python
import requests
import base64
import json
response = requests.post(
@ -379,19 +380,58 @@ response = requests.post(
"input": "Hello world!",
"voice": "af_bella",
"speed": 1.0,
"response_format": "wav"
}
"response_format": "mp3",
"stream": False,
},
stream=False
)
# Get timestamps from header
timestamps = json.loads(response.headers['X-Word-Timestamps'])
print("Word-level timestamps:")
for ts in timestamps:
print(f"{ts['word']}: {ts['start_time']:.3f}s - {ts['end_time']:.3f}s")
with open("output.mp3","wb") as f:
# Save audio
with open("output.wav", "wb") as f:
f.write(response.content)
audio_json=json.loads(response.content)
# Decode base 64 stream to bytes
chunk_audio=base64.b64decode(audio_json["audio"].encode("utf-8"))
# Process streaming chunks
f.write(chunk_audio)
# Print word level timestamps
print(audio_json["timestamps"])
```
Generate audio with word-level timestamps with streaming:
```python
import requests
import base64
import json
response = requests.post(
"http://localhost:8880/dev/captioned_speech",
json={
"model": "kokoro",
"input": "Hello world!",
"voice": "af_bella",
"speed": 1.0,
"response_format": "mp3",
"stream": True,
},
stream=True
)
f=open("output.mp3","wb")
for chunk in response.iter_lines(decode_unicode=True):
if chunk:
chunk_json=json.loads(chunk)
# Decode base 64 stream to bytes
chunk_audio=base64.b64decode(chunk_json["audio"].encode("utf-8"))
# Process streaming chunks
f.write(chunk_audio)
# Print word level timestamps
print(chunk_json["timestamps"])
```
</details>

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

@ -23,7 +23,7 @@ class AudioChunk:
for audio_chunk in audio_chunk_list[1:]:
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
output.word_timestamps+=audio_chunk.word_timestamps
return output

56
api/src/routers/development.py
View file

@ -1,9 +1,10 @@
import re
from typing import List, Union, AsyncGenerator, Tuple
import numpy as np
import torch
from fastapi import APIRouter, Depends, Header, HTTPException, Request, Response
from fastapi.responses import StreamingResponse, FileResponse
from fastapi.responses import JSONResponse, StreamingResponse, FileResponse
from kokoro import KPipeline
from loguru import logger
@ -156,40 +157,6 @@ async def generate_from_phonemes(
},
)
@router.get("/dev/timestamps/{filename}")
async def get_timestamps(filename: str):
"""Download timestamps from temp storage"""
try:
from ..core.paths import _find_file
# Search for file in temp directory
file_path = await _find_file(
filename=filename, search_paths=[settings.temp_file_dir]
)
return FileResponse(
file_path,
media_type="application/json",
filename=filename,
headers={
"Cache-Control": "no-cache",
"Content-Disposition": f"attachment; filename={filename}",
},
)
except Exception as e:
logger.error(f"Error serving timestamps file {filename}: {e}")
raise HTTPException(
status_code=500,
detail={
"error": "server_error",
"message": "Failed to serve timestamps file",
"type": "server_error",
},
)
@router.post("/dev/captioned_speech")
async def create_captioned_speech(
request: CaptionedSpeechRequest,
@ -245,8 +212,9 @@ async def create_captioned_speech(
async for chunk,chunk_data in generator:
if chunk: # Skip empty chunks
await temp_writer.write(chunk)
base64_chunk= base64.b64encode(chunk).decode("utf-8")
yield chunk
yield CaptionedSpeechResponse(audio=base64_chunk,audio_format=content_type,timestamps=chunk_data.word_timestamps)
# Finalize the temp file
await temp_writer.finalize()
@ -272,13 +240,11 @@ async def create_captioned_speech(
# Encode the chunk bytes into base 64
base64_chunk= base64.b64encode(chunk).decode("utf-8")
yield CaptionedSpeechResponse(audio=base64_chunk,audio_format=content_type,words=chunk_data.word_timestamps)
yield CaptionedSpeechResponse(audio=base64_chunk,audio_format=content_type,timestamps=chunk_data.word_timestamps)
except Exception as e:
logger.error(f"Error in single output streaming: {e}")
raise
# NEED TO DO REPLACE THE RETURN WITH A JSON OBJECT CONTAINING BOTH THE FILE AND THE WORD TIMESTAMPS
# Standard streaming without download link
return JSONStreamingResponse(
single_output(),
@ -296,6 +262,8 @@ async def create_captioned_speech(
text=request.input,
voice=voice_name,
speed=request.speed,
return_timestamps=request.return_timestamps,
normalization_options=request.normalization_options,
lang_code=request.lang_code,
)
@ -316,9 +284,13 @@ async def create_captioned_speech(
is_last_chunk=True,
)
output=content+final
return Response(
content=output,
media_type=content_type,
base64_output= base64.b64encode(output).decode("utf-8")
content=CaptionedSpeechResponse(audio=base64_output,audio_format=content_type,timestamps=audio_data.word_timestamps).model_dump()
return JSONResponse(
content=content,
media_type="application/json",
headers={
"Content-Disposition": f"attachment; filename=speech.{request.response_format}",
"Cache-Control": "no-cache", # Prevent caching

2
api/src/routers/openai_compatible.py
View file

@ -282,8 +282,10 @@ async def create_speech(
text=request.input,
voice=voice_name,
speed=request.speed,
normalization_options=request.normalization_options,
lang_code=request.lang_code,
)
content, audio_data = await AudioService.convert_audio(
audio_data,
24000,

7
api/src/services/tts_service.py
View file

@ -333,20 +333,17 @@ class TTSService:
voice: str,
speed: float = 1.0,
return_timestamps: bool = False,
normalization_options: Optional[NormalizationOptions] = NormalizationOptions(),
lang_code: Optional[str] = None,
) -> Tuple[Tuple[np.ndarray,AudioChunk]]:
"""Generate complete audio for text using streaming internally."""
start_time = time.time()
audio_data_chunks=[]
try:
async for _,audio_stream_data in self.generate_audio_stream(text,voice,speed=speed,return_timestamps=return_timestamps,lang_code=lang_code,output_format=None):
async for _,audio_stream_data in self.generate_audio_stream(text,voice,speed=speed,normalization_options=normalization_options,return_timestamps=return_timestamps,lang_code=lang_code,output_format=None):
audio_data_chunks.append(audio_stream_data)
combined_audio_data=AudioChunk.combine(audio_data_chunks)
return combined_audio_data.audio,combined_audio_data
"""

2
api/src/structures/schemas.py
View file

@ -35,7 +35,7 @@ class CaptionedSpeechResponse(BaseModel):
audio: str = Field(..., description="The generated audio data encoded in base 64")
audio_format: str = Field(..., description="The format of the output audio")
words: List[WordTimestamp] = Field(..., description="Word-level timestamps")
timestamps: Optional[List[WordTimestamp]] = Field(..., description="Word-level timestamps")
class NormalizationOptions(BaseModel):
"""Options for the normalization system"""

32
examples/captioned_speech_example.py
View file

@ -2,6 +2,7 @@ import json
from typing import Tuple, Optional, Dict, List
from pathlib import Path
import base64
import requests
# Get the directory this script is in
@ -9,9 +10,9 @@ SCRIPT_DIR = Path(__file__).absolute().parent
def generate_captioned_speech(
text: str,
voice: str = "af_bella",
voice: str = "af_heart",
speed: float = 1.0,
response_format: str = "wav"
response_format: str = "mp3"
) -> Tuple[Optional[bytes], Optional[List[Dict]]]:
"""Generate audio with word-level timestamps."""
response = requests.post(
@ -21,40 +22,31 @@ def generate_captioned_speech(
"input": text,
"voice": voice,
"speed": speed,
"response_format": response_format
"response_format": response_format,
"stream": False
}
)
print(f"Response status: {response.status_code}")
print(f"Response headers: {dict(response.headers)}")
if response.status_code != 200:
print(f"Error response: {response.text}")
return None, None
try:
# Get timestamps path from header
timestamps_filename = response.headers.get('X-Timestamps-Path')
if not timestamps_filename:
print("Error: No timestamps path in response headers")
return None, None
audio_json=json.loads(response.content)
# Get timestamps from the path
timestamps_response = requests.get(f"http://localhost:8880/dev/timestamps/{timestamps_filename}")
if timestamps_response.status_code != 200:
print(f"Error getting timestamps: {timestamps_response.text}")
return None, None
# Decode base 64 stream to bytes
chunk_audio=base64.b64decode(audio_json["audio"].encode("utf-8"))
word_timestamps = timestamps_response.json()
# Print word level timestamps
print(audio_json["timestamps"])
# Get audio bytes from content
audio_bytes = response.content
if not audio_bytes:
if not chunk_audio:
print("Error: Empty audio content")
return None, None
return audio_bytes, word_timestamps
return chunk_audio, audio_json["timestamps"]
except json.JSONDecodeError as e:
print(f"Error parsing timestamps: {e}")
return None, None