added generate image via nserver, refactor

2025-11-20 12:56:27 +01:00 · 2023-11-20 19:17:10 +01:00
parent ad1cee97e2
commit 5a3f5606df
16 changed files with 493 additions and 100 deletions
--- a/tasks/imagegenerationsdxl.py
+++ b/tasks/imagegenerationsdxl.py
@@ -0,0 +1,120 @@
+import os
+from multiprocessing.pool import ThreadPool
+from backends.nova_server import check_nova_server_status, send_request_to_nova_server
+from interfaces.dvmtaskinterface import DVMTaskInterface
+from utils.definitions import EventDefinitions
+from utils.nip89_utils import NIP89Announcement
+
+
+"""
+This File contains a Module to transform Text input on NOVA-Server and receive results back. 
+
+Accepted Inputs: Prompt (text)
+Outputs: An url to an Image
+"""
+
+
+class ImageGenerationSDXL(DVMTaskInterface):
+    KIND: int = EventDefinitions.KIND_NIP90_GENERATE_IMAGE
+    TASK: str = "text-to-image"
+    COST: int = 0
+
+    def __init__(self, name, pk):
+        self.NAME = name
+        self.PK = pk
+
+    def NIP89_announcement(self, d_tag, content):
+        nip89 = NIP89Announcement()
+        nip89.kind = self.KIND
+        nip89.pk = self.PK
+        nip89.dtag = d_tag
+        nip89.content = content
+        return nip89
+
+    def is_input_supported(self, input_type, input_content):
+        if input_type != "text":
+            return False
+        return True
+
+    def create_request_form_from_nostr_event(self, event, client=None, dvm_config=None):
+        request_form = {"jobID": event.id().to_hex() + "_"+ self.NAME.replace(" ", "")}
+        request_form["mode"] = "PROCESS"
+        request_form["trainerFilePath"] = 'modules\\stablediffusionxl\\stablediffusionxl.trainer'
+
+        prompt = ""
+        negative_prompt = ""
+        #model = "stabilityai/stable-diffusion-xl-base-1.0"
+        model = "unstable"
+        # models: juggernautXL, dynavisionXL, colossusProjectXL, newrealityXL, unstable
+        ratio_width = "1"
+        ratio_height = "1"
+        width = ""
+        height = ""
+        lora = ""
+        lora_weight = ""
+        strength = ""
+        guidance_scale = ""
+        for tag in event.tags():
+            if tag.as_vec()[0] == 'i':
+                input_type = tag.as_vec()[2]
+                if input_type == "text":
+                    prompt = tag.as_vec()[1]
+
+            elif tag.as_vec()[0] == 'param':
+                print(tag.as_vec()[2])
+                if tag.as_vec()[1] == "negative_prompt":
+                    negative_prompt = tag.as_vec()[2]
+                elif tag.as_vec()[1] == "lora":
+                    lora = tag.as_vec()[2]
+                elif tag.as_vec()[1] == "lora_weight":
+                    lora_weight = tag.as_vec()[2]
+                elif tag.as_vec()[1] == "strength":
+                    strength = tag.as_vec()[2]
+                elif tag.as_vec()[1] == "guidance_scale":
+                    guidance_scale = tag.as_vec()[2]
+                elif tag.as_vec()[1] == "ratio":
+                    if len(tag.as_vec()) > 3:
+                        ratio_width = (tag.as_vec()[2])
+                        ratio_height = (tag.as_vec()[3])
+                    elif len(tag.as_vec()) == 3:
+                        split = tag.as_vec()[2].split(":")
+                        ratio_width = split[0]
+                        ratio_height = split[1]
+                    #if size is set it will overwrite ratio.
+                elif tag.as_vec()[1] == "size":
+
+                    if len(tag.as_vec()) > 3:
+                         width = (tag.as_vec()[2])
+                         height = (tag.as_vec()[3])
+                    elif len(tag.as_vec()) == 3:
+                        split = tag.as_vec()[2].split("x")
+                        if len(split) > 1:
+                            width = split[0]
+                            height = split[1]
+                            print(width)
+                            print(height)
+                elif tag.as_vec()[1] == "model":
+                    model = tag.as_vec()[2]
+
+        prompt = prompt.replace(";", ",")
+        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"}]'
+        request_form["optStr"] = ('model=' + model + ';ratio=' + str(ratio_width) + '-' + str(ratio_height) + ';size=' +
+                                  str(width) + '-' + str(height) + ';strength=' + str(strength) + ';guidance_scale=' +
+                                  str(guidance_scale) + ';lora=' + lora + ';lora_weight=' + lora_weight)
+
+        return request_form
+
+    def process(self, request_form):
+        try:
+            # Call the process route of NOVA-Server with our request form.
+            success = send_request_to_nova_server(request_form, os.environ["NOVA_SERVER"])
+            print(success)
+
+            pool = ThreadPool(processes=1)
+            thread = pool.apply_async(check_nova_server_status, (request_form['jobID'], os.environ["NOVA_SERVER"]))
+            print("Wait for results of NOVA-Server...")
+            result = thread.get()
+            return str(result)
+
+        except Exception as e:
+            raise Exception(e)