File size: 9,150 Bytes
cd0ff97 1f36bcf cd0ff97 1f36bcf cd0ff97 1f36bcf cd0ff97 3921761 cd0ff97 3921761 cd0ff97 3921761 cd0ff97 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 | import base64
import os
import tempfile
from pathlib import Path
from typing import Any, Dict, List
from uuid import uuid4
import fastapi
import modal
from fastapi import Header, HTTPException
from fastapi.responses import Response
from backend.magpie_adapter import MagpieAdapter
from backend.omnivoice_adapter import OmniVoiceAdapter
from backend.synthesis_catalog import MODAL_BACKEND
from backend.types import VoiceConfig
app = modal.App("scriptorium-tts")
image = (
modal.Image.debian_slim(python_version="3.12")
.apt_install("git")
.pip_install(
"fastapi[standard]",
"numpy>=1.26.0",
"soundfile>=0.13.0",
"torch>=2.8.0",
"torchaudio>=2.8.0",
"omnivoice>=0.1.5",
"requests>=2.32.0",
"huggingface_hub>=0.33.0",
"nemo_toolkit[tts]@git+https://github.com/NVIDIA/NeMo.git@main",
"kaldialign",
)
.add_local_python_source("backend")
)
jobs = modal.Dict.from_name("scriptorium-modal-jobs", create_if_missing=True)
artifacts = modal.Dict.from_name("scriptorium-modal-artifacts", create_if_missing=True)
web_app = fastapi.FastAPI()
def _check_auth(header: str | None) -> None:
expected = os.getenv("SCRIPTORIUM_MODAL_SHARED_SECRET", "").strip()
if not expected:
return
token = (header or "").removeprefix("Bearer ").strip()
if token != expected:
raise HTTPException(status_code=401, detail="Unauthorized")
def _adapter_for(model: str):
if model == "magpie":
return MagpieAdapter()
return OmniVoiceAdapter()
def _voice_config(payload: Dict[str, Any], temp_dir: Path) -> VoiceConfig:
data = dict(payload)
sample_b64 = data.pop("sample_b64", None)
voice = VoiceConfig.from_dict(data)
if sample_b64:
sample_path = temp_dir / "clone-sample.wav"
sample_path.write_bytes(base64.b64decode(sample_b64))
voice.sample_path = str(sample_path)
return voice
@app.function(image=image, gpu="any", timeout=900)
def render_preview(payload: Dict[str, Any]) -> Dict[str, Any]:
with tempfile.TemporaryDirectory() as tmp:
temp_dir = Path(tmp)
output_path = temp_dir / "preview.wav"
voice = _voice_config(payload["voice_config"], temp_dir)
result = _adapter_for(voice.model).synthesize(
text=str(payload["text"]),
output_path=output_path,
voice_config=voice,
diffusion_steps=int(payload.get("diffusion_steps", 32)),
speed=float(payload.get("speed", 1.0)),
)
return {
"audio_base64": base64.b64encode(output_path.read_bytes()).decode("ascii"),
"duration_seconds": result.get("duration_seconds", 0),
"sample_rate": result.get("sample_rate", 24000),
"backend": MODAL_BACKEND,
"model": voice.model,
}
def _job_state(job_id: str) -> Dict[str, Any]:
raw = jobs.get(
job_id,
{
"status": "pending",
"events": [],
"cancel_requested": False,
},
)
if raw is None:
return {
"status": "pending",
"events": [],
"cancel_requested": False,
}
if not isinstance(raw, dict):
raise RuntimeError(f"Corrupt job state for {job_id}: expected dict, got {type(raw).__name__}")
return dict(raw)
def _save_job_state(job_id: str, state: Dict[str, Any]) -> None:
jobs[job_id] = state
def _append_event(job_id: str, event: Dict[str, Any]) -> None:
state = _job_state(job_id)
state.setdefault("events", []).append(event)
state["status"] = event.get("type", state.get("status", "running"))
_save_job_state(job_id, state)
@app.function(image=image, gpu="any", timeout=60 * 60)
def render_book(job_id: str, payload: Dict[str, Any]) -> None:
with tempfile.TemporaryDirectory() as tmp:
temp_dir = Path(tmp)
voice = _voice_config(payload["voice_config"], temp_dir)
chapters = [chapter for chapter in payload["chapters"] if chapter.get("included", True)]
state = _job_state(job_id)
state["status"] = "running"
_save_job_state(job_id, state)
_append_event(
job_id,
{
"type": "started",
"session_id": payload["session_id"],
"total_chapters": len(chapters),
"book_title": payload["book"].get("title"),
"backend": MODAL_BACKEND,
"model": voice.model,
},
)
adapter = _adapter_for(voice.model)
outputs: List[str] = []
for index, chapter in enumerate(chapters):
state = _job_state(job_id)
if state.get("cancel_requested"):
_append_event(
job_id,
{
"type": "cancelled",
"session_id": payload["session_id"],
"backend": MODAL_BACKEND,
"model": voice.model,
},
)
return
chapter_id = str(chapter["id"])
_append_event(
job_id,
{
"type": "chapter_started",
"session_id": payload["session_id"],
"chapter_id": chapter_id,
"chapter_title": chapter["title"],
"chapter_index": index,
"overall_progress": index / max(1, len(chapters)),
"backend": MODAL_BACKEND,
"model": voice.model,
},
)
output_path = temp_dir / f"{index + 1:03d}-{chapter_id}.wav"
result = adapter.synthesize(
text=str(chapter["text"]),
output_path=output_path,
voice_config=voice,
diffusion_steps=int(payload.get("diffusion_steps", 32)),
speed=float(payload.get("speed", 1.0)),
)
filename = output_path.name
artifacts[f"{job_id}:{filename}"] = output_path.read_bytes()
outputs.append(filename)
_append_event(
job_id,
{
"type": "chapter_done",
"session_id": payload["session_id"],
"chapter_id": chapter_id,
"duration_seconds": int(result.get("duration_seconds", 0)),
"overall_progress": (index + 1) / max(1, len(chapters)),
"filename": filename,
"artifact_url": f"/artifacts/{job_id}/{filename}",
"backend": MODAL_BACKEND,
"model": voice.model,
},
)
_append_event(
job_id,
{
"type": "completed",
"session_id": payload["session_id"],
"outputs": outputs,
"backend": MODAL_BACKEND,
"model": voice.model,
},
)
@web_app.post("/preview")
def preview_endpoint(
payload: Dict[str, Any],
authorization: str | None = Header(default=None),
) -> Dict[str, Any]:
_check_auth(authorization)
return render_preview.remote(payload)
@web_app.post("/renders")
def submit_render_endpoint(
payload: Dict[str, Any],
authorization: str | None = Header(default=None),
) -> Dict[str, str]:
_check_auth(authorization)
job_id = str(uuid4())
_save_job_state(job_id, {"status": "pending", "events": [], "cancel_requested": False})
render_book.spawn(job_id, payload)
return {"job_id": job_id}
@web_app.get("/renders/{job_id}")
def render_status_endpoint(
job_id: str,
cursor: int = 0,
authorization: str | None = Header(default=None),
) -> Dict[str, Any]:
_check_auth(authorization)
try:
state = _job_state(job_id)
events = list(state.get("events", []))
return {
"job_id": job_id,
"status": state.get("status", "pending"),
"events": events[cursor:],
}
except Exception as exc:
raise HTTPException(status_code=500, detail=f"Unable to fetch render status for {job_id}: {exc}") from exc
@web_app.post("/renders/{job_id}/cancel")
def cancel_render_endpoint(
job_id: str,
authorization: str | None = Header(default=None),
) -> Dict[str, str]:
_check_auth(authorization)
state = _job_state(job_id)
state["cancel_requested"] = True
state["status"] = "cancelled"
_save_job_state(job_id, state)
return {"type": "cancelled", "job_id": job_id}
@web_app.get("/artifacts/{job_id}/{filename}")
def artifact_endpoint(
job_id: str,
filename: str,
authorization: str | None = Header(default=None),
):
_check_auth(authorization)
content = artifacts.get(f"{job_id}:{filename}")
if content is None:
raise HTTPException(status_code=404, detail="Artifact not found")
return Response(content=content, media_type="audio/wav")
@app.function(image=image)
@modal.asgi_app()
def fastapi_app():
return web_app
|