Package with uv, add config
This commit is contained in:
Lee Braiden
parent
5ec9871b65
commit
bf3d37c5d9
12 changed files with 1143 additions and 228 deletions
2
.gitignore
vendored
2
.gitignore
vendored
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@ -1,7 +1,7 @@
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__pycache__/
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*.pyo
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*.pyc
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output/*
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outputs/*
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dist/
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.venv/
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.python-version
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25
README.md
25
README.md
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@ -61,28 +61,17 @@ git clone https://github.com/Lex-au/Orpheus-FastAPI.git
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cd Orpheus-FastAPI
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```
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2. Create a Python virtual environment:
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2. Install `pipx`
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```bash
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# Using venv (Python's built-in virtual environment)
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python -m venv venv
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source venv/bin/activate # On Windows: venv\Scripts\activate
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# Or using conda
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conda create -n orpheus-tts python=3.10
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conda activate orpheus-tts
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sudo apt-get install pipx
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```
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3. Install PyTorch with CUDA support:
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3. Install `uv`
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```bash
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pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124
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pipx install uv
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```
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4. Install other dependencies:
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```bash
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pip3 install -r requirements.txt
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```
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5. Set up the required directories:
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4. Set up the required directories:
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```bash
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# Create directories for outputs and static files
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mkdir -p outputs static
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@ -92,12 +81,12 @@ mkdir -p outputs static
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Run the FastAPI server:
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```bash
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python app.py
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uv run orpheus-fastapi
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```
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Or with specific host/port:
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```bash
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uvicorn app:app --host 0.0.0.0 --port 5005 --reload
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uv run orpheus-fastapi --host 0.0.0.0 --port 5005
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```
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170
app.py
170
app.py
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@ -1,170 +0,0 @@
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# Orpheus-FASTAPI by Lex-au
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# https://github.com/Lex-au/Orpheus-FastAPI
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# Description: Main FastAPI server for Orpheus Text-to-Speech
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import os
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import time
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from datetime import datetime
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from typing import List, Optional
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from fastapi import FastAPI, Request, Form, HTTPException, Depends
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from fastapi.responses import HTMLResponse, FileResponse, JSONResponse
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from fastapi.staticfiles import StaticFiles
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from fastapi.templating import Jinja2Templates
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from pydantic import BaseModel
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from tts_engine import generate_speech_from_api, AVAILABLE_VOICES, DEFAULT_VOICE
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# Create FastAPI app
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app = FastAPI(
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title="Orpheus-FASTAPI",
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description="High-performance Text-to-Speech server using Orpheus-FASTAPI",
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version="1.0.0"
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)
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# Ensure directories exist
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os.makedirs("outputs", exist_ok=True)
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os.makedirs("static", exist_ok=True)
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# Mount directories for serving files
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app.mount("/outputs", StaticFiles(directory="outputs"), name="outputs")
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app.mount("/static", StaticFiles(directory="static"), name="static")
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# Setup templates
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templates = Jinja2Templates(directory="templates")
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# API models
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class SpeechRequest(BaseModel):
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input: str
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model: str = "orpheus"
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voice: str = DEFAULT_VOICE
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response_format: str = "wav"
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speed: float = 1.0
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class APIResponse(BaseModel):
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status: str
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voice: str
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output_file: str
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generation_time: float
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# OpenAI-compatible API endpoint
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@app.post("/v1/audio/speech")
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async def create_speech_api(request: SpeechRequest):
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"""
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Generate speech from text using the Orpheus TTS model.
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Compatible with OpenAI's /v1/audio/speech endpoint.
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"""
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if not request.input:
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raise HTTPException(status_code=400, detail="Missing input text")
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# Generate unique filename
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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output_path = f"outputs/{request.voice}_{timestamp}.wav"
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# Generate speech
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start = time.time()
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generate_speech_from_api(
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prompt=request.input,
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voice=request.voice,
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output_file=output_path
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)
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end = time.time()
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generation_time = round(end - start, 2)
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# Return audio file
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return FileResponse(
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path=output_path,
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media_type="audio/wav",
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filename=f"{request.voice}_{timestamp}.wav"
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)
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# Legacy API endpoint for compatibility
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@app.post("/speak")
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async def speak(request: Request):
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"""Legacy endpoint for compatibility with existing clients"""
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data = await request.json()
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text = data.get("text", "")
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voice = data.get("voice", DEFAULT_VOICE)
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if not text:
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return JSONResponse(
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status_code=400,
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content={"error": "Missing 'text'"}
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)
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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output_path = f"outputs/{voice}_{timestamp}.wav"
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# Generate speech
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start = time.time()
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generate_speech_from_api(prompt=text, voice=voice, output_file=output_path)
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end = time.time()
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generation_time = round(end - start, 2)
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return JSONResponse(content={
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"status": "ok",
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"voice": voice,
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"output_file": output_path,
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"generation_time": generation_time
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})
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# Web UI routes
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@app.get("/", response_class=HTMLResponse)
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async def root(request: Request):
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"""Redirect to web UI"""
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return templates.TemplateResponse(
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"tts.html",
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{"request": request, "voices": AVAILABLE_VOICES}
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)
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@app.get("/web/", response_class=HTMLResponse)
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async def web_ui(request: Request):
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"""Main web UI for TTS generation"""
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return templates.TemplateResponse(
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"tts.html",
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{"request": request, "voices": AVAILABLE_VOICES}
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)
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@app.post("/web/", response_class=HTMLResponse)
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async def generate_from_web(
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request: Request,
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text: str = Form(...),
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voice: str = Form(DEFAULT_VOICE)
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):
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"""Handle form submission from web UI"""
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if not text:
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return templates.TemplateResponse(
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"tts.html",
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{
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"request": request,
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"error": "Please enter some text.",
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"voices": AVAILABLE_VOICES
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}
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)
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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output_path = f"outputs/{voice}_{timestamp}.wav"
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# Generate speech
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start = time.time()
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generate_speech_from_api(prompt=text, voice=voice, output_file=output_path)
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end = time.time()
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generation_time = round(end - start, 2)
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return templates.TemplateResponse(
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"tts.html",
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{
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"request": request,
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"success": True,
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"text": text,
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"voice": voice,
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"output_file": output_path,
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"generation_time": generation_time,
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"voices": AVAILABLE_VOICES
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}
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)
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if __name__ == "__main__":
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import uvicorn
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print("🔥 Starting Orpheus-FASTAPI Server (CUDA)")
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uvicorn.run("app:app", host="0.0.0.0", port=5005, reload=True)
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29
pyproject.toml
Normal file
29
pyproject.toml
Normal file
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[project]
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name = "orpheus-fastapi"
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version = "0.1.0"
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description = "Add your description here"
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readme = "README.md"
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authors = []
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requires-python = ">=3.12"
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dependencies = [
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"fastapi>=0.103.1",
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"jinja2>=3.1.2",
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"numpy>=1.24.0",
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"pydantic>=2.3.0",
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"python-multipart>=0.0.6",
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"requests>=2.31.0",
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"snac>=0.3.0",
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"sounddevice>=0.4.6",
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"torch",
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"torchaudio",
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"torchvision",
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"uvicorn>=0.23.2",
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]
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[project.scripts]
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orpheus-fastapi = "orpheus_fastapi.__main__:main"
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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# Core dependencies
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fastapi>=0.103.1
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uvicorn>=0.23.2
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jinja2>=3.1.2
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pydantic>=2.3.0
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numpy>=1.24.0
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requests>=2.31.0
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sounddevice>=0.4.6
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python-multipart>=0.0.6
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# SNAC is required for audio generation from tokens
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snac>=0.3.0
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# PyTorch - Note: Install PyTorch with CUDA 12.4 support separately:
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# pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124
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0
src/orpheus_fastapi/__init__.py
Normal file
0
src/orpheus_fastapi/__init__.py
Normal file
271
src/orpheus_fastapi/__main__.py
Normal file
271
src/orpheus_fastapi/__main__.py
Normal file
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@ -0,0 +1,271 @@
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# Orpheus-FASTAPI by Lex-au
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# https://github.com/Lex-au/Orpheus-FastAPI
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# Description: Main FastAPI server for Orpheus Text-to-Speech
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import argparse
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import logging
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import os
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import sys
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import time
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from datetime import datetime
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from typing import List, Optional, AsyncIterator
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from pathlib import Path
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from contextlib import asynccontextmanager
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from urllib.parse import urljoin
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import uvicorn
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from fastapi import FastAPI, Request, Form, HTTPException, Depends
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from fastapi.responses import HTMLResponse, FileResponse, JSONResponse
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from fastapi.staticfiles import StaticFiles
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from fastapi.templating import Jinja2Templates
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from pydantic import BaseModel
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from .inference import generate_speech_from_api, AVAILABLE_VOICES, DEFAULT_VOICE
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OUTPUTS_PATH = Path(__name__).parent.parent.parent.absolute() / 'outputs'
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STATIC_PATH = Path(__name__).parent.parent.parent.absolute() / 'static'
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class Config:
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def __init__(self, host: str, port: int, api_url: str, templates_dir: Path):
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self.host = host
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self.port = port
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self.api_url = api_url
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self.templates = Jinja2Templates(directory=templates_dir)
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def apply_to(self, func):
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def wrapper(*args, **kwargs):
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return func(self, *args, **kwargs)
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return wrapper
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@classmethod
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def from_args(cls, args) -> 'Config':
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arg_parser = argparse.ArgumentParser()
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arg_parser.add_argument("--host", "-H", default="127.0.0.1", help="Hostname (or IP) to provide OpenAI-compatible TTS services on")
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arg_parser.add_argument("--port", "-P", default="5005", type=int, help="Port to provide OpenAI-compatible TTS services on")
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arg_parser.add_argument("--api-url", "-A", default="http://localhost:1337", help="URL of the inference server running the Orpheus model")
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parsed_args = arg_parser.parse_args(args)
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return cls(
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host=parsed_args.host,
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port=parsed_args.port,
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api_url=parsed_args.api_url,
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templates_dir=(Path(__file__).parent.parent.parent / 'templates').absolute(),
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)
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class ThisApp(FastAPI):
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def __init__(self, *args, **kwargs):
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super().__init__(*args, **kwargs)
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self.config = Config.from_args(sys.argv[1:])
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# API models
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class SpeechRequest(BaseModel):
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input: str
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model: str = "orpheus"
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voice: str = DEFAULT_VOICE
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response_format: str = "wav"
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speed: float = 1.0
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class APIResponse(BaseModel):
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status: str
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voice: str
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output_file: str
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generation_time: float
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# Create FastAPI app
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app = ThisApp(
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title="Orpheus-FASTAPI",
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description="High-performance Text-to-Speech server using Orpheus-FASTAPI",
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version="1.0.0",
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)
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# OpenAI-compatible API endpoint
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@app.post("/v1/audio/speech")
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async def create_speech_api(app_request: Request, speech_request: SpeechRequest):
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"""
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Generate speech from text using the Orpheus TTS model.
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Compatible with OpenAI's /v1/audio/speech endpoint.
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"""
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if not speech_request.input:
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raise HTTPException(status_code=400, detail="Missing input text")
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# Generate unique filename
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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output_path = OUTPUTS_PATH / f"{speech_request.voice}_{timestamp}.wav"
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output_url = urljoin('/outputs/', output_path.name)
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# Generate speech
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start = time.time()
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generate_speech_from_api(
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prompt=speech_request.input,
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voice=speech_request.voice,
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output_file=str(output_url),
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api_url=app_request.app.config.api_url,
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)
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end = time.time()
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generation_time = round(end - start, 2)
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# Return audio file
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return FileResponse(
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path=str(output_path),
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media_type="audio/wav",
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filename=f"{speech_request.voice}_{timestamp}.wav"
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)
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# Legacy API endpoint for compatibility
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@app.post("/speak")
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async def speak(request: Request):
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"""Legacy endpoint for compatibility with existing clients"""
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data = await request.json()
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text = data.get("text", "")
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voice = data.get("voice", DEFAULT_VOICE)
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if not text:
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return JSONResponse(
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status_code=400,
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content={"error": "Missing 'text'"}
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)
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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output_path = OUTPUTS_PATH / f"{voice}_{timestamp}.wav"
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# Generate speech
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start = time.time()
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generate_speech_from_api(prompt=text, voice=voice, output_file=str(output_path), api_url=request.app.config.api_url)
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end = time.time()
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generation_time = round(end - start, 2)
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output_url = urljoin('/outputs/', output_path.name)
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return JSONResponse(content={
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"status": "ok",
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"voice": voice,
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"output_file": str(output_url),
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"generation_time": generation_time
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})
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# Web UI routes
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@app.get("/", response_class=HTMLResponse)
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async def root(request: Request):
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"""Redirect to web UI"""
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return request.app.config.templates.TemplateResponse(
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"tts.html",
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{"request": request, "voices": AVAILABLE_VOICES}
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)
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@app.get("/web/", response_class=HTMLResponse)
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async def web_ui(request: Request):
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"""Main web UI for TTS generation"""
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return request.app.config.templates.TemplateResponse(
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"tts.html",
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{"request": request, "voices": AVAILABLE_VOICES}
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)
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@app.post("/web/", response_class=HTMLResponse)
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async def generate_from_web(
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request: Request,
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text: str = Form(...),
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voice: str = Form(DEFAULT_VOICE)
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):
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"""Handle form submission from web UI"""
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if not text:
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return request.app.config.templates.TemplateResponse(
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"tts.html",
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{
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"request": request,
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"error": "Please enter some text.",
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"voices": AVAILABLE_VOICES
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}
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)
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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output_path = OUTPUTS_PATH / f"{voice}_{timestamp}.wav"
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# Generate speech
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start = time.time()
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generate_speech_from_api(prompt=text, voice=voice, output_file=output_path, api_url=request.app.config.api_url)
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end = time.time()
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generation_time = round(end - start, 2)
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output_url = urljoin('/outputs/', output_path.name)
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return request.app.config.templates.TemplateResponse(
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"tts.html",
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{
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"request": request,
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"success": True,
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"text": text,
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"voice": voice,
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"output_file": str(output_url),
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"generation_time": generation_time,
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"voices": AVAILABLE_VOICES
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}
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)
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|
||||
def path_is_within(input_path: Path, allowed_path: Path) -> bool:
|
||||
"""
|
||||
Confirm that input_path is within allowed_path in absolute terms after resolving symlinks in allowed_path.
|
||||
|
||||
Args:
|
||||
allowed_path (Path): The path within which input_path must be contained, after symlink resolution.
|
||||
input_path (Path): The path to check, absolute or relative.
|
||||
|
||||
Returns:
|
||||
bool: True if the resolved input_path is within the resolved allowed_path, False otherwise.
|
||||
"""
|
||||
# Convert input_path to absolute if it's relative, then resolve symlinks
|
||||
resolved_input_path = input_path.absolute().resolve()
|
||||
# Resolve allowed_path to its real, absolute location, following symlinks
|
||||
resolved_allowed_path = allowed_path.resolve()
|
||||
|
||||
# Check if resolved_input_path is a subpath of resolved_allowed_path
|
||||
try:
|
||||
resolved_input_path.relative_to(resolved_allowed_path)
|
||||
return True
|
||||
except ValueError:
|
||||
# ValueError is raised if resolved_input_path is not within resolved_allowed_path
|
||||
return False
|
||||
|
||||
|
||||
@app.get('/outputs/{file_name}')
|
||||
def get_outputs(request: Request, file_name: str):
|
||||
assert os.pathsep not in file_name, "didn't think FastAPI would allow this; need to handle it properly then."
|
||||
file_path = OUTPUTS_PATH / file_name
|
||||
|
||||
assert path_is_within(file_path, OUTPUTS_PATH), "FATAL ERROR: unexpected directory traversal would have occurred! Aborting."
|
||||
|
||||
return FileResponse(file_path)
|
||||
|
||||
|
||||
@app.get('/static/{file_name}')
|
||||
def get_static(request: Request, file_name: str):
|
||||
assert os.pathsep not in file_name, "didn't think FastAPI would allow this; need to handle it properly then."
|
||||
file_path = STATIC_PATH / file_name
|
||||
|
||||
assert path_is_within(file_path, STATIC_PATH), "FATAL ERROR: unexpected directory traversal would have occurred! Aborting."
|
||||
|
||||
return FileResponse(file_path)
|
||||
|
||||
|
||||
def main():
|
||||
logging.basicConfig()
|
||||
|
||||
# Ensure output directory exists
|
||||
os.makedirs(OUTPUTS_PATH, exist_ok=True)
|
||||
|
||||
print("🔥 Starting Orpheus-FASTAPI Server (CUDA)")
|
||||
print(f" Serving OpenAI-compatible Speech API on {app.config.host}:{app.config.port}")
|
||||
print(f" Using OpenAI compatible Orpheus text generation API at {app.config.api_url}")
|
||||
print(f" Using output directory {OUTPUTS_PATH}")
|
||||
|
||||
uvicorn.run(f"{__name__}:app", host="0.0.0.0", port=5005, reload=True, log_level='trace')
|
||||
|
||||
|
|
@ -23,8 +23,9 @@ if torch.cuda.is_available():
|
|||
print(f"High-end GPU detected: {torch.cuda.get_device_name(0)}")
|
||||
print("Enabling high-performance optimizations")
|
||||
|
||||
DEFAULT_API_URL = "http://127.0.0.1:1337/v1/completions"
|
||||
|
||||
# Orpheus-FASTAPI settings - make configurable for different endpoints
|
||||
API_URL = os.environ.get("ORPHEUS_API_URL", "http://your-server-ip:port/v1/completions or v1/chat/completions")
|
||||
HEADERS = {
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
|
@ -109,7 +110,8 @@ def format_prompt(prompt: str, voice: str = DEFAULT_VOICE) -> str:
|
|||
|
||||
def generate_tokens_from_api(prompt: str, voice: str = DEFAULT_VOICE, temperature: float = TEMPERATURE,
|
||||
top_p: float = TOP_P, max_tokens: int = MAX_TOKENS,
|
||||
repetition_penalty: float = REPETITION_PENALTY) -> Generator[str, None, None]:
|
||||
repetition_penalty: float = REPETITION_PENALTY,
|
||||
api_url: str=DEFAULT_API_URL) -> Generator[str, None, None]:
|
||||
"""Generate tokens from text using OpenAI-compatible API with optimized streaming and retry logic."""
|
||||
start_time = time.time()
|
||||
formatted_prompt = format_prompt(prompt, voice)
|
||||
|
|
@ -141,7 +143,7 @@ def generate_tokens_from_api(prompt: str, voice: str = DEFAULT_VOICE, temperatur
|
|||
try:
|
||||
# Make the API request with streaming and timeout
|
||||
response = session.post(
|
||||
API_URL,
|
||||
api_url,
|
||||
headers=HEADERS,
|
||||
json=payload,
|
||||
stream=True,
|
||||
|
|
@ -205,7 +207,7 @@ def generate_tokens_from_api(prompt: str, voice: str = DEFAULT_VOICE, temperatur
|
|||
return
|
||||
|
||||
except requests.exceptions.ConnectionError:
|
||||
print(f"Connection error to API at {API_URL}")
|
||||
print(f"Connection error to API at {api_url}")
|
||||
retry_count += 1
|
||||
if retry_count < max_retries:
|
||||
wait_time = 2 ** retry_count
|
||||
|
|
@ -462,7 +464,7 @@ def stream_audio(audio_buffer):
|
|||
print(f"Audio playback error: {e}")
|
||||
|
||||
def generate_speech_from_api(prompt, voice=DEFAULT_VOICE, output_file=None, temperature=TEMPERATURE,
|
||||
top_p=TOP_P, max_tokens=MAX_TOKENS, repetition_penalty=REPETITION_PENALTY):
|
||||
top_p=TOP_P, max_tokens=MAX_TOKENS, repetition_penalty=REPETITION_PENALTY, api_url: str=DEFAULT_API_URL):
|
||||
"""Generate speech from text using Orpheus model with performance optimizations."""
|
||||
print(f"Starting speech generation for '{prompt[:50]}{'...' if len(prompt) > 50 else ''}'")
|
||||
print(f"Using voice: {voice}, GPU acceleration: {'Yes (High-end)' if HIGH_END_GPU else 'Yes' if torch.cuda.is_available() else 'No'}")
|
||||
|
|
@ -481,7 +483,8 @@ def generate_speech_from_api(prompt, voice=DEFAULT_VOICE, output_file=None, temp
|
|||
temperature=temperature,
|
||||
top_p=top_p,
|
||||
max_tokens=max_tokens,
|
||||
repetition_penalty=repetition_penalty
|
||||
repetition_penalty=repetition_penalty,
|
||||
api_url=api_url,
|
||||
),
|
||||
output_file=output_file
|
||||
)
|
||||
|
|
@ -510,6 +513,7 @@ def main():
|
|||
parser.add_argument("--text", type=str, help="Text to convert to speech")
|
||||
parser.add_argument("--voice", type=str, default=DEFAULT_VOICE, help=f"Voice to use (default: {DEFAULT_VOICE})")
|
||||
parser.add_argument("--output", type=str, help="Output WAV file path")
|
||||
parser.add_argument("--api-url", type=str, default=DEFAULT_API_URL, help="Inference server API URL")
|
||||
parser.add_argument("--list-voices", action="store_true", help="List available voices")
|
||||
parser.add_argument("--temperature", type=float, default=TEMPERATURE, help="Temperature for generation")
|
||||
parser.add_argument("--top_p", type=float, default=TOP_P, help="Top-p sampling parameter")
|
||||
|
|
@ -550,7 +554,8 @@ def main():
|
|||
temperature=args.temperature,
|
||||
top_p=args.top_p,
|
||||
repetition_penalty=args.repetition_penalty,
|
||||
output_file=output_file
|
||||
output_file=output_file,
|
||||
api_url=args.api_url,
|
||||
)
|
||||
end_time = time.time()
|
||||
|
||||
|
|
@ -369,7 +369,7 @@
|
|||
responsive: true
|
||||
});
|
||||
|
||||
wavesurfer.load('/' + audioPath);
|
||||
wavesurfer.load(audioPath);
|
||||
|
||||
wavesurfer.on('ready', function() {
|
||||
const duration = wavesurfer.getDuration();
|
||||
|
|
@ -419,7 +419,7 @@
|
|||
// Set values
|
||||
document.getElementById('voice-name').textContent = response.voice.charAt(0).toUpperCase() + response.voice.slice(1);
|
||||
document.getElementById('generation-time').textContent = response.generation_time;
|
||||
document.getElementById('download-link').href = '/' + response.output_file;
|
||||
document.getElementById('download-link').href = response.output_file;
|
||||
|
||||
// Initialize waveform
|
||||
initWaveSurfer(response.output_file);
|
||||
|
|
|
|||
|
|
@ -1,15 +0,0 @@
|
|||
"""
|
||||
TTS Engine package for Orpheus text-to-speech system.
|
||||
|
||||
This package contains the core components for audio generation:
|
||||
- inference.py: Token generation and API handling
|
||||
- speechpipe.py: Audio conversion pipeline
|
||||
"""
|
||||
|
||||
# Make key components available at package level
|
||||
from .inference import (
|
||||
generate_speech_from_api,
|
||||
AVAILABLE_VOICES,
|
||||
DEFAULT_VOICE,
|
||||
list_available_voices
|
||||
)
|
||||
821
uv.lock
Normal file
821
uv.lock
Normal file
|
|
@ -0,0 +1,821 @@
|
|||
version = 1
|
||||
revision = 1
|
||||
requires-python = ">=3.12"
|
||||
|
||||
[[package]]
|
||||
name = "annotated-types"
|
||||
version = "0.7.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081 }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643 },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "anyio"
|
||||
version = "4.9.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "idna" },
|
||||
{ name = "sniffio" },
|
||||
{ name = "typing-extensions", marker = "python_full_version < '3.13'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/95/7d/4c1bd541d4dffa1b52bd83fb8527089e097a106fc90b467a7313b105f840/anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028", size = 190949 }
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||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/a1/ee/48ca1a7c89ffec8b6a0c5d02b89c305671d5ffd8d3c94acf8b8c408575bb/anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c", size = 100916 },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2025.1.31"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/1c/ab/c9f1e32b7b1bf505bf26f0ef697775960db7932abeb7b516de930ba2705f/certifi-2025.1.31.tar.gz", hash = "sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651", size = 167577 }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/38/fc/bce832fd4fd99766c04d1ee0eead6b0ec6486fb100ae5e74c1d91292b982/certifi-2025.1.31-py3-none-any.whl", hash = "sha256:ca78db4565a652026a4db2bcdf68f2fb589ea80d0be70e03929ed730746b84fe", size = 166393 },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "cffi"
|
||||
version = "1.17.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "pycparser" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/fc/97/c783634659c2920c3fc70419e3af40972dbaf758daa229a7d6ea6135c90d/cffi-1.17.1.tar.gz", hash = "sha256:1c39c6016c32bc48dd54561950ebd6836e1670f2ae46128f67cf49e789c52824", size = 516621 }
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||||
wheels = [
|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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Loading…
Reference in a new issue