Spaces:
Running on Zero
Running on Zero
File size: 2,732 Bytes
02ad302 5b7cd5f 02ad302 5b7cd5f 02ad302 | 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 | """
ZeroGPU-compatible entrypoint using gradio.Server.
Server extends FastAPI, so all your existing API routes work unchanged.
"""
from __future__ import annotations
import os
# 1. Lightweight imports only at top level
import spaces
import gradio as gr
from gradio import Server
from gradio.data_classes import FileData
from fastapi import Request
from slowapi.errors import RateLimitExceeded
from slowapi import _rate_limit_exceeded_handler
TTS_ENGINE = os.getenv("TTS_ENGINE", "chatterbox").lower()
# 2. Create Server instead of FastAPI
# Name it 'demo' so HF Space picks it up automatically
demo = Server()
# -----------------------------------------------------
# INTEGRATE SERVER.PY ROUTES
# -----------------------------------------------------
from server import router, limiter, enforce_content_length_limit
from tools_api import router as tools_router
demo.include_router(router)
demo.include_router(tools_router)
demo.state.limiter = limiter
demo.add_exception_handler(RateLimitExceeded, _rate_limit_exceeded_handler)
# Apply content length middleware to the main app
@demo.middleware("http")
async def content_length_middleware(request: Request, call_next):
return await enforce_content_length_limit(request, call_next)
@demo.get("/api/health")
def health():
return {"status": "ok", "tts": TTS_ENGINE}
# -----------------------------------------------------
# ZERO GPU FUNCTION — lazy-loads torch/CUDA
# -----------------------------------------------------
@spaces.GPU(duration=60)
def run_pipeline(job_id: str):
from pipeline import process_job
return process_job(job_id)
# -----------------------------------------------------
# GRADIO API INTEGRATION (this is what ZeroGPU detects)
# -----------------------------------------------------
@demo.api(name="run_pipeline")
def api_run_pipeline(job_id: str):
"""
Exposed through Gradio's API engine.
ZeroGPU will allocate a GPU when this endpoint is called.
"""
return run_pipeline(job_id)
# -----------------------------------------------------
# OPTIONAL: Gradio UI (if you still want a basic UI)
# -----------------------------------------------------
with gr.Blocks(title="VideoVoice API") as ui:
gr.Markdown(f"# VideoVoice API ({TTS_ENGINE.upper()})")
job_id_box = gr.Textbox(label="Job ID")
output_box = gr.Textbox(label="Result")
btn = gr.Button("Run Pipeline")
btn.click(fn=run_pipeline, inputs=job_id_box, outputs=output_box)
# Mount the UI onto the Server instance
gr.mount_gradio_app(demo, ui, path="/ui")
# -----------------------------------------------------
# ENTRYPOINT
# -----------------------------------------------------
if __name__ == "__main__":
demo.launch(show_error=True) |