some options, configurable paths

api/serve.py

@@ -1,24 +1,48 @@
 from diffusers import OnnxStableDiffusionPipeline
-from flask import Flask
+from flask import Flask, request, send_file
+from io import BytesIO
+from os import environ, path, makedirs
 
+# defaults
+empty_prompt = "a photo of an astronaut eating a hamburger"
 max_height = 512
 max_width = 512
+max_steps = 50
+max_cfg = 8
 
+# paths
+model_path = environ.get('ONNX_WEB_MODEL_PATH', "../../stable_diffusion_onnx")
+output_path = environ.get('ONNX_WEB_OUTPUT_PATH', "../../web_output")
+
+def setup():
+  if not path.exists(model_path):
+    raise RuntimeError('model path must exist')
+  if not path.exists(output_path):
+    makedirs(output_path)
+
+# setup
+setup()
 app = Flask(__name__)
-pipe = OnnxStableDiffusionPipeline.from_pretrained("./stable_diffusion_onnx", provider="DmlExecutionProvider", safety_checker=None)
+pipe = OnnxStableDiffusionPipeline.from_pretrained(model_path, provider="DmlExecutionProvider", safety_checker=None)
-
 
+# routes
 @app.route('/')
 def hello():
-    return 'Hello, World!'
+    return 'Hello, %s' % (__name__)
 
 @app.route('/txt2img')
 def txt2img():
+  prompt = request.args.get('prompt', empty_prompt)
   height = request.args.get('height', max_height)
   width = request.args.get('width', max_width)
-  prompt = request.args.get('prompt', "a photo of an astronaut eating a hamburger")
+  steps = int(request.args.get('steps', max_steps))
-  steps = 50
+  cfg = int(request.args.get('cfg', max_cfg))
-  cfg = 8
 
+  print("txt2img: %s/%s, %sx%s, %s" % (cfg, steps, width, height, prompt))
   image = pipe(prompt, height, width, num_inference_steps=steps, guidance_scale=cfg).images[0]
-  image.save("astronaut_rides_horse.png")
+  # image.save("astronaut_rides_horse.png")
+
+  img_io = BytesIO()
+  image.save(img_io, 'PNG', quality=100)
+  img_io.seek(0)
+  return send_file(img_io, mimetype='image/png')