add seed and guidance scale

main.py

@@ -1,6 +1,8 @@
 import os
 import time
 import sys
+import re
+import random
 import torch
 from fastapi import FastAPI
 from fastapi.staticfiles import StaticFiles
@@ -27,8 +29,15 @@ def draw(data: Data):
 	if data.member_secret != "" and data.member_secret == os.environ.get("MEMBER_SECRET"):
 		print(f"Is CUDA available: {torch.cuda.is_available()}")
 
-		# prompt = '(('+data.string+')) (( photograph )), highly detailed, sharp focus, 8k, 4k, (( photorealism )), detailed, saturated, portrait, 50mm, F/2.8, 1m away, ( global illumination, studio light, volumetric light ), ((( multicolor lights )))'
-		prompt = '(('+data.string+')) (( photograph )), highly detailed, sharp focus, 8k, 4k, (( photorealism )), detailed, saturated, portrait, 50mm, F/2.8, 1m away, ((( multicolor lights )))'
+		text = re.sub('^#', '', data.string)
+
+		if '_seed' in text:
+		  seed = 1024
+		else:
+		  seed = random.randrange(1024)
+
+		# prompt = '(('+text+')) (( photograph )), highly detailed, sharp focus, 8k, 4k, (( photorealism )), detailed, saturated, portrait, 50mm, F/2.8, 1m away, ( global illumination, studio light, volumetric light ), ((( multicolor lights )))'
+		prompt = '(('+text+')) (( photograph )), highly detailed, sharp focus, 8k, 4k, (( photorealism )), detailed, saturated, portrait, 50mm, F/2.8, 1m away, ((( multicolor lights )))'
 		n_prompt = 'text, blurry, art, painting, rendering, drawing, sketch, (( ugly )), (( duplicate )), ( morbid ), (( mutilated )), ( mutated ), ( deformed ), ( disfigured ), ( extra limbs ), ( malformed limbs ), ( missing arms ), ( missing legs ), ( extra arms ), ( extra legs ), ( fused fingers ), ( too many fingers ), long neck, low quality, worst quality'
 
 		# https://huggingface.co/docs/hub/spaces-sdks-docker-first-demo
@@ -41,7 +50,8 @@ def draw(data: Data):
 		pipe = StableDiffusionPipeline.from_pretrained(model_id, revision='fp16', torch_dtype=torch.float16)
 		pipe = pipe.to('cuda')
 
-		image = pipe(prompt, negative_prompt=n_prompt).images[0]
+		generator = torch.Generator("cuda").manual_seed(seed)
+		image = pipe(prompt, negative_prompt=n_prompt, guidance_scale=7.5, generator=generator).images[0]
 
 		fileName = "sd_" + str(time.time()) + '.png'
 		image.save("/code/tmpdir/" + fileName)