added generate image via nserver, refactor

tasks/README.md

@@ -0,0 +1,13 @@
+# NostrAI Data Vending Machine Tasks
+
+Here Tasks can be defined. Tasks need to follow the DVMTaskInterface as defined in interfaces. 
+Tasks can either happen locally (especially if they are fast) or they can call an alternative backend.
+Reusable backend functions can be defined in backends (e.g. API calls)
+
+Current List of Tasks:
+
+| Module              | Kind | Description                               | Backend                   |
+|---------------------|------|-------------------------------------------|---------------------------|
+| Translation         | 5002 | Translates Inputs to another language     | Local, calling Google API |
+| TextExtractionPDF   | 5001 | Extracts Text from a PDF file             | Local                     |
+| ImageGenerationSDXL | 5100 | Generates an Image with StableDiffusionXL | nova-server               |

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)

tasks/textextractionpdf.py

@@ -2,12 +2,16 @@ import os
 import re
 
 from interfaces.dvmtaskinterface import DVMTaskInterface
-from utils import env
 from utils.definitions import EventDefinitions
 from utils.nip89_utils import NIP89Announcement
-from utils.nostr_utils import get_event_by_id, get_referenced_event_by_id
+from utils.nostr_utils import get_event_by_id
 
+"""
+This File contains a Module to extract Text from a PDF file locally on the DVM Machine
 
+Accepted Inputs: Url to pdf file, Event containing an URL to a PDF file
+Outputs: Text containing the extracted contents of the PDF file
+"""
 class TextExtractionPDF(DVMTaskInterface):
     KIND: int = EventDefinitions.KIND_NIP90_EXTRACT_TEXT
     TASK: str = "pdf-to-text"
@@ -17,16 +21,16 @@ class TextExtractionPDF(DVMTaskInterface):
         self.NAME = name
         self.PK = pk
 
-    def NIP89_announcement(self):
+    def NIP89_announcement(self, d_tag, content):
         nip89 = NIP89Announcement()
         nip89.kind = self.KIND
         nip89.pk = self.PK
-        nip89.dtag = os.getenv(env.TASK_TEXTEXTRACTION_NIP89_DTAG)
-        nip89.content = "{\"name\":\"" + self.NAME + "\",\"image\":\"https://image.nostr.build/c33ca6fc4cc038ca4adb46fdfdfda34951656f87ee364ef59095bae1495ce669.jpg\",\"about\":\"I extract Text from pdf documents\",\"nip90Params\":{}}"
+        nip89.dtag = d_tag
+        nip89.content = content
         return nip89
 
     def is_input_supported(self, input_type, input_content):
-        if input_type != "url":
+        if input_type != "url" and input_type != "event":
             return False
         return True
 
@@ -45,23 +49,21 @@ class TextExtractionPDF(DVMTaskInterface):
 
         if input_type == "url":
             url = input_content
+        # if event contains url to pdf, we checked for a pdf link before
         elif input_type == "event":
             evt = get_event_by_id(input_content, config=dvm_config)
             url = re.search("(?P<url>https?://[^\s]+)", evt.content()).group("url")
-        elif input_type == "job":
-            evt = get_referenced_event_by_id(input_content, [EventDefinitions.KIND_NIP90_RESULT_GENERATE_IMAGE],
-                                             client, config=dvm_config)
-
-            url = re.search("(?P<url>https?://[^\s]+)", evt.content()).group("url")
 
         request_form["optStr"] = 'url=' + url
         return request_form
 
     def process(self, request_form):
-        options = DVMTaskInterface.setOptions(request_form)
         from pypdf import PdfReader
         from pathlib import Path
         import requests
+
+        options = DVMTaskInterface.setOptions(request_form)
+
         try:
             file_path = Path('temp.pdf')
             response = requests.get(options["url"])
@@ -76,4 +78,4 @@ class TextExtractionPDF(DVMTaskInterface):
             os.remove('temp.pdf')
             return text
         except Exception as e:
-            raise Exception(e)
+            raise Exception(e)

tasks/translation.py

@@ -1,12 +1,19 @@
 import os
 
 from interfaces.dvmtaskinterface import DVMTaskInterface
-from utils import env
 from utils.definitions import EventDefinitions
 from utils.nip89_utils import NIP89Announcement
 from utils.nostr_utils import get_referenced_event_by_id, get_event_by_id
 
 
+"""
+This File contains a Module to call Google Translate Services locally on the DVM Machine
+
+Accepted Inputs: Text, Events, Jobs (Text Extraction, Summary, Translation)
+Outputs: Text containing the Translation in the desired language.
+"""
+
+
 class Translation(DVMTaskInterface):
     KIND: int = EventDefinitions.KIND_NIP90_TRANSLATE_TEXT
     TASK: str = "translation"
@@ -16,12 +23,12 @@ class Translation(DVMTaskInterface):
         self.NAME = name
         self.PK = pk
 
-    def NIP89_announcement(self):
+    def NIP89_announcement(self, d_tag, content):
         nip89 = NIP89Announcement()
         nip89.kind = self.KIND
         nip89.pk = self.PK
-        nip89.dtag = os.getenv(env.TASK_TRANSLATION_NIP89_DTAG)
-        nip89.content = "{\"name\":\"" + self.NAME + "\",\"image\":\"https://image.nostr.build/c33ca6fc4cc038ca4adb46fdfdfda34951656f87ee364ef59095bae1495ce669.jpg\",\"about\":\"I translate text from given text/event/job, currently using Google Translation Services into language defined in param.  \",\"nip90Params\":{\"language\":{\"required\":true,\"values\":[\"af\",\"am\",\"ar\",\"az\",\"be\",\"bg\",\"bn\",\"bs\",\"ca\",\"ceb\",\"co\",\"cs\",\"cy\",\"da\",\"de\",\"el\",\"eo\",\"es\",\"et\",\"eu\",\"fa\",\"fi\",\"fr\",\"fy\",\"ga\",\"gd\",\"gl\",\"gu\",\"ha\",\"haw\",\"hi\",\"hmn\",\"hr\",\"ht\",\"hu\",\"hy\",\"id\",\"ig\",\"is\",\"it\",\"he\",\"ja\",\"jv\",\"ka\",\"kk\",\"km\",\"kn\",\"ko\",\"ku\",\"ky\",\"la\",\"lb\",\"lo\",\"lt\",\"lv\",\"mg\",\"mi\",\"mk\",\"ml\",\"mn\",\"mr\",\"ms\",\"mt\",\"my\",\"ne\",\"nl\",\"no\",\"ny\",\"or\",\"pa\",\"pl\",\"ps\",\"pt\",\"ro\",\"ru\",\"sd\",\"si\",\"sk\",\"sl\",\"sm\",\"sn\",\"so\",\"sq\",\"sr\",\"st\",\"su\",\"sv\",\"sw\",\"ta\",\"te\",\"tg\",\"th\",\"tl\",\"tr\",\"ug\",\"uk\",\"ur\",\"uz\",\"vi\",\"xh\",\"yi\",\"yo\",\"zh\",\"zu\"]}}}"
+        nip89.dtag = d_tag
+        nip89.content = content
         return nip89
 
     def is_input_supported(self, input_type, input_content):
@@ -65,7 +72,8 @@ class Translation(DVMTaskInterface):
                 if tag.as_vec()[0] == 'i':
                     evt = get_referenced_event_by_id(tag.as_vec()[1],
                                                      [EventDefinitions.KIND_NIP90_RESULT_EXTRACT_TEXT,
-                                                      EventDefinitions.KIND_NIP90_RESULT_SUMMARIZE_TEXT],
+                                                      EventDefinitions.KIND_NIP90_RESULT_SUMMARIZE_TEXT,
+                                                      EventDefinitions.KIND_NIP90_RESULT_TRANSLATE_TEXT],
                                                      client,
                                                      config=dvm_config)
                     text = evt.content()
@@ -77,8 +85,9 @@ class Translation(DVMTaskInterface):
         return request_form
 
     def process(self, request_form):
-        options = DVMTaskInterface.setOptions(request_form)
         from translatepy.translators.google import GoogleTranslate
+
+        options = DVMTaskInterface.setOptions(request_form)
         gtranslate = GoogleTranslate()
         length = len(options["text"])