mirror of
https://github.com/believethehype/nostrdvm.git
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131 lines
5.2 KiB
Python
131 lines
5.2 KiB
Python
import os
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from multiprocessing.pool import ThreadPool
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from threading import Thread
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from backends.nova_server import check_nova_server_status, send_request_to_nova_server
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from dvm import DVM
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from interfaces.dvmtaskinterface import DVMTaskInterface
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from utils.definitions import EventDefinitions
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"""
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This File contains a Module to transform Text input on NOVA-Server and receive results back.
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Accepted Inputs: Prompt (text)
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Outputs: An url to an Image
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"""
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class ImageGenerationSDXL(DVMTaskInterface):
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NAME: str
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KIND: int = EventDefinitions.KIND_NIP90_GENERATE_IMAGE
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TASK: str = "text-to-image"
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COST: int = 5
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PK: str
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def __init__(self, name, dvm_config, default_model=None, default_lora=None):
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self.NAME = name
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dvm_config.SUPPORTED_TASKS = [self]
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dvm_config.DB = "db/" + self.NAME + ".db"
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self.PK = dvm_config.PRIVATE_KEY
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self.default_model = default_model
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self.default_lora = default_lora
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dvm = DVM
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nostr_dvm_thread = Thread(target=dvm, args=[dvm_config])
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nostr_dvm_thread.start()
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def is_input_supported(self, input_type, input_content):
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if input_type != "text":
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return False
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return True
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def create_request_form_from_nostr_event(self, event, client=None, dvm_config=None):
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request_form = {"jobID": event.id().to_hex() + "_"+ self.NAME.replace(" ", "")}
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request_form["trainerFilePath"] = 'modules\\stablediffusionxl\\stablediffusionxl.trainer'
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prompt = ""
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negative_prompt = ""
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if self.default_model is None:
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model = "stabilityai/stable-diffusion-xl-base-1.0"
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else:
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model = self.default_model
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# models: juggernautXL, dynavisionXL, colossusProjectXL, newrealityXL, unstable
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ratio_width = "1"
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ratio_height = "1"
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width = ""
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height = ""
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if self.default_lora == None:
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lora = ""
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else:
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lora = self.default_lora
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lora_weight = ""
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strength = ""
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guidance_scale = ""
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for tag in event.tags():
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if tag.as_vec()[0] == 'i':
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input_type = tag.as_vec()[2]
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if input_type == "text":
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prompt = tag.as_vec()[1]
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elif tag.as_vec()[0] == 'param':
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print(tag.as_vec()[2])
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if tag.as_vec()[1] == "negative_prompt":
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negative_prompt = tag.as_vec()[2]
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elif tag.as_vec()[1] == "lora":
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lora = tag.as_vec()[2]
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elif tag.as_vec()[1] == "lora_weight":
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lora_weight = tag.as_vec()[2]
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elif tag.as_vec()[1] == "strength":
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strength = tag.as_vec()[2]
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elif tag.as_vec()[1] == "guidance_scale":
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guidance_scale = tag.as_vec()[2]
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elif tag.as_vec()[1] == "ratio":
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if len(tag.as_vec()) > 3:
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ratio_width = (tag.as_vec()[2])
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ratio_height = (tag.as_vec()[3])
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elif len(tag.as_vec()) == 3:
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split = tag.as_vec()[2].split(":")
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ratio_width = split[0]
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ratio_height = split[1]
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#if size is set it will overwrite ratio.
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elif tag.as_vec()[1] == "size":
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if len(tag.as_vec()) > 3:
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width = (tag.as_vec()[2])
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height = (tag.as_vec()[3])
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elif len(tag.as_vec()) == 3:
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split = tag.as_vec()[2].split("x")
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if len(split) > 1:
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width = split[0]
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height = split[1]
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print(width)
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print(height)
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elif tag.as_vec()[1] == "model":
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model = tag.as_vec()[2]
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prompt = prompt.replace(";", ",")
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request_form['data'] = '[{"id":"input_prompt","type":"input","src":"request:text","data":"' + prompt + '","active":"True"},{"id":"negative_prompt","type":"input","src":"request:text","data":"' + negative_prompt + '","active":"True"},{"id":"output_image","type":"output","src":"request:image","active":"True"}]'
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request_form["optStr"] = ('model=' + model + ';ratio=' + str(ratio_width) + '-' + str(ratio_height) + ';size=' +
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str(width) + '-' + str(height) + ';strength=' + str(strength) + ';guidance_scale=' +
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str(guidance_scale) + ';lora=' + lora + ';lora_weight=' + lora_weight)
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return request_form
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def process(self, request_form):
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try:
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# Call the process route of NOVA-Server with our request form.
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success = send_request_to_nova_server(request_form, os.environ["NOVA_SERVER"])
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print(success)
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pool = ThreadPool(processes=1)
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thread = pool.apply_async(check_nova_server_status, (request_form['jobID'], os.environ["NOVA_SERVER"]))
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print("Wait for results of NOVA-Server...")
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result = thread.get()
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return str(result)
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except Exception as e:
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raise Exception(e)
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