103 lines
2.0 KiB
Python
103 lines
2.0 KiB
Python
import threading
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import os
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import websocket
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from contextlib import asynccontextmanager
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from fastapi import FastAPI
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from fastapi.responses import FileResponse
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from fastapi.staticfiles import StaticFiles
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# the index of the current audio track from 0 to 9
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current_index = -1
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# the timer that periodically advances the current audio track
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t = None
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# websocket connection to the inference server
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ws = None
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prompts = [
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"gentle, calming lo-fi beats that helps with studying and focusing",
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"calm, piano lo-fi beats to help with studying and focusing",
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"gentle lo-fi hip-hop to relax to",
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"gentle, quiet synthwave lo-fi beats",
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"morning lo-fi beats",
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]
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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global ws
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url = os.environ.get("INFERENCE_SERVER_WS_URL")
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if not url:
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url = "ws://localhost:8001"
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ws = websocket.create_connection(url)
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print(f"websocket connected to {url}")
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advance()
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yield
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if ws:
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ws.close()
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if t:
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t.cancel()
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def generate_new_audio():
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if not ws:
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return
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global current_index
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offset = 0
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if current_index == 0:
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offset = 5
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elif current_index == 5:
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offset = 0
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else:
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return
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print("generating new audio...")
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ws.send("generate")
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wavs = []
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for i in range(5):
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raw = ws.recv()
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if isinstance(raw, str):
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continue
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wavs.append(raw)
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for i, wav in enumerate(wavs):
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with open(f"{i + offset}.mp3", "wb") as f:
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f.write(wav)
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print("audio generated.")
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def advance():
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global current_index, t
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if current_index == 9:
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current_index = 0
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else:
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current_index = current_index + 1
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threading.Thread(target=generate_new_audio).start()
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t = threading.Timer(60, advance)
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t.start()
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app = FastAPI(lifespan=lifespan)
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@app.get("/current.mp3")
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def get_current_audio():
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print("hello")
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return FileResponse(f"{current_index}.mp3")
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app.mount("/", StaticFiles(directory="web", html=True), name="web")
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