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#!/usr/bin/env python3
# Copyright (C) 2026 Danilo M. <danix@danix.xyz>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License version 2 as
# published by the Free Software Foundation.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# Long-lived daemon that keeps ONE SDXL model resident in XPU VRAM so prompt
# iteration skips the model-reload tax. Stdlib HTTP only. Serial by design:
# one GPU, so concurrent generation would OOM. See README.md.
import io
import json
import os
import sys
from http.server import BaseHTTPRequestHandler, HTTPServer
import torch
import generate
PORT = int(os.environ.get("IMGGEN_PORT", "8765"))
STATE = {"model": None, "pipe": None}
def load(model_key):
if STATE["model"] == model_key and STATE["pipe"] is not None:
return
if STATE["pipe"] is not None:
del STATE["pipe"]
STATE["pipe"] = None
STATE["model"] = None
torch.xpu.empty_cache()
STATE["pipe"] = generate.build_pipe(model_key)
STATE["model"] = model_key
class Handler(BaseHTTPRequestHandler):
def _json(self, code, obj):
body = json.dumps(obj).encode()
self.send_response(code)
self.send_header("Content-Type", "application/json")
self.send_header("Content-Length", str(len(body)))
self.end_headers()
self.wfile.write(body)
def _read_json(self):
length = int(self.headers.get("Content-Length", "0"))
raw = self.rfile.read(length) if length else b"{}"
return json.loads(raw) # raises on bad JSON -> caught by caller
def do_GET(self):
if self.path == "/status":
self._json(200, {"model": STATE["model"], "ready": STATE["pipe"] is not None})
else:
self._json(404, {"error": "not found"})
def do_POST(self):
try:
data = self._read_json()
except (ValueError, json.JSONDecodeError):
self._json(400, {"error": "bad JSON"})
return
if self.path == "/model":
name = data.get("name")
try:
generate.resolve_model(name)
except SystemExit as e:
self._json(400, {"error": str(e)})
return
try:
load(name)
except Exception as e: # download / load failure
self._json(500, {"error": f"load failed: {e}"})
return
self._json(200, {"model": STATE["model"], "ready": True})
return
if self.path == "/generate":
try:
image, elapsed = generate.generate(
STATE["pipe"],
data["prompt"],
data.get("negative", ""),
int(data.get("steps", 25)),
float(data.get("guidance", 7.0)),
data.get("seed"),
int(data.get("width", 1024)),
int(data.get("height", 1024)),
)
except torch.OutOfMemoryError:
torch.xpu.empty_cache()
self._json(500, {"error": "OOM, try fewer steps or smaller size"})
return
except Exception as e:
self._json(500, {"error": str(e)})
return
buf = io.BytesIO()
image.save(buf, format="PNG")
body = buf.getvalue()
self.send_response(200)
self.send_header("Content-Type", "image/png")
self.send_header("X-Elapsed", f"{elapsed:.2f}")
self.send_header("Content-Length", str(len(body)))
self.end_headers()
self.wfile.write(body)
return
self._json(404, {"error": "not found"})
def log_message(self, fmt, *args):
sys.stderr.write("%s - %s\n" % (self.address_string(), fmt % args))
def main():
startup = os.environ.get("IMGGEN_MODEL", generate.DEFAULT_MODEL)
print(f"Loading {startup} on XPU ...", file=sys.stderr)
load(startup)
print(f"Ready on 127.0.0.1:{PORT} with model {startup}", file=sys.stderr)
HTTPServer(("0.0.0.0", PORT), Handler).serve_forever()
if __name__ == "__main__":
main()
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