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https://github.com/believethehype/nostrdvm.git
synced 2025-11-19 01:26:31 +01:00
added dall-e, reworked bot, added nip89config
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Believethehype
160
tasks/imagegeneration_sdxl.py
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160
tasks/imagegeneration_sdxl.py
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import json
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from multiprocessing.pool import ThreadPool
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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.admin_utils import AdminConfig
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from utils.definitions import EventDefinitions
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from utils.dvmconfig import DVMConfig
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from utils.nip89_utils import NIP89Config
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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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Params: -model # models: juggernaut, dynavision, colossusProject, newreality, unstable
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-lora # loras (weights on top of models) voxel,
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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 = 50
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PK: str
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DVM = DVM
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def __init__(self, name, dvm_config: DVMConfig, nip89config: NIP89Config, admin_config: AdminConfig = None, options=None):
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self.NAME = name
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self.PK = dvm_config.PRIVATE_KEY
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dvm_config.SUPPORTED_DVMS = [self]
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dvm_config.DB = "db/" + self.NAME + ".db"
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dvm_config.NIP89 = self.NIP89_announcement(nip89config)
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self.dvm_config = dvm_config
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self.admin_config = admin_config
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self.options = options
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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.options.get("default_model"):
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model = self.options['default_model']
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else:
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model = "stabilityai/stable-diffusion-xl-base-1.0"
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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.options.get("default_lora"):
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lora = self.options['default_lora']
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else:
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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("Param: " + tag.as_vec()[1] + ": " + 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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elif tag.as_vec()[1] == "model":
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model = tag.as_vec()[2]
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io_input = {
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"id": "input_prompt",
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"type": "input",
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"src": "request:text",
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"data": prompt
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}
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io_negative = {
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"id": "negative_prompt",
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"type": "input",
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"src": "request:text",
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"data": negative_prompt
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}
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io_output = {
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"id": "output_image",
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"type": "output",
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"src": "request:image"
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}
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request_form['data'] = json.dumps([io_input, io_negative, io_output])
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options = {
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"model": model,
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"ratio": ratio_width + '-' + ratio_height,
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"width": width,
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"height": height,
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"strength": strength,
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"guidance_scale": guidance_scale,
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"lora": lora,
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"lora_weight": lora_weight
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}
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request_form['options'] = json.dumps(options)
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# old format, deprecated, will remove
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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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response = send_request_to_nova_server(request_form, self.options['nova_server'])
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if bool(json.loads(response)['success']):
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print("Job " + request_form['jobID'] + " sent to NOVA-server")
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pool = ThreadPool(processes=1)
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thread = pool.apply_async(check_nova_server_status, (request_form['jobID'], self.options['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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