updating to latest changes

main.py

@@ -1,12 +1,13 @@
 import os
 from pathlib import Path
 import dotenv
+from sys import platform
 
 from nostr_dvm.bot import Bot
 from nostr_dvm.tasks import videogeneration_replicate_svd, imagegeneration_replicate_sdxl, textgeneration_llmlite, \
     trending_notes_nostrband, discovery_inactive_follows, translation_google, textextraction_pdf, \
     translation_libretranslate, textextraction_google, convert_media, imagegeneration_openai_dalle, texttospeech, \
-    imagegeneration_mlx, advanced_search, textextraction_whisper_mlx
+    imagegeneration_sd21_mlx, advanced_search
 from nostr_dvm.utils.admin_utils import AdminConfig
 from nostr_dvm.utils.backend_utils import keep_alive
 from nostr_dvm.utils.definitions import EventDefinitions
@@ -139,10 +140,10 @@ def playground():
     bot_config.SUPPORTED_DVMS.append(tts)
     tts.run()
 
-    from sys import platform
+
     if platform == "darwin":
         # Test with MLX for OSX M1/M2/M3 chips
-        mlx = imagegeneration_mlx.build_example("SD with MLX", "mlx_sd", admin_config)
+        mlx = imagegeneration_sd21_mlx.build_example("SD with MLX", "mlx_sd", admin_config)
         bot_config.SUPPORTED_DVMS.append(mlx)
         mlx.run()
 

nostr_dvm/backends/nova_server/utils.py

@@ -11,7 +11,7 @@ from nostr_dvm.utils.output_utils import upload_media_to_hoster
 
 """
 This file contains basic calling functions for ML tasks that are outsourced to nova server. It is an Open-Source backend
-that enables running models locally based on preefined modules, by accepting a request form.
+that enables running models locally based on preefined modules, by accepting a request.
 Modules are deployed in in separate virtual environments so dependencies won't conflict. 
 """
 

nostr_dvm/tasks/imagegeneration_sd21_mlx.py

@@ -12,7 +12,7 @@ from nostr_dvm.utils.output_utils import upload_media_to_hoster
 from nostr_dvm.utils.zap_utils import get_price_per_sat
 
 """
-This File contains a Module to generate an Image on replicate and receive results back. 
+This File contains a Module to generate an Image on Macs with M1/M2/M3 chips and receive results back. 
 
 Accepted Inputs: Prompt (text)
 Outputs: An url to an Image
@@ -95,7 +95,7 @@ class ImageGenerationMLX(DVMTaskInterface):
     def process(self, request_form):
         try:
             import mlx.core as mx
-            from backends.mlx.stable_diffusion import StableDiffusion
+            from nostr_dvm.backends.mlx.modules.stable_diffusion import StableDiffusion
             options = DVMTaskInterface.set_options(request_form)
 
             sd = StableDiffusion()

nostr_dvm/tasks/imagegeneration_sdxl.py

@@ -171,6 +171,7 @@ class ImageGenerationSDXL(DVMTaskInterface):
 def build_example(name, identifier, admin_config, server_address, default_model="stabilityai/stable-diffusion-xl"
                                                                                    "-base-1.0", default_lora=""):
     dvm_config = build_default_config(identifier)
+    dvm_config.USE_OWN_VENV = False
     admin_config.LUD16 = dvm_config.LN_ADDRESS
     # A module might have options it can be initialized with, here we set a default model, and the server
     # address it should use. These parameters can be freely defined in the task component
@@ -202,18 +203,13 @@ def build_example(name, identifier, admin_config, server_address, default_model=
                                admin_config=admin_config, options=options)
 
 
+def process_venv():
+    args = DVMTaskInterface.process_args()
+    dvm_config = build_default_config(args.identifier)
+    dvm = ImageGenerationSDXL(name="", dvm_config=dvm_config, nip89config=NIP89Config(), admin_config=None)
+    result = dvm.process(json.loads(args.request))
+    DVMTaskInterface.write_output(result, args.output)
+
+
 if __name__ == '__main__':
-    env_path = Path('.env')
+    process_venv()
-    if env_path.is_file():
-        print(f'loading environment from {env_path.resolve()}')
-        dotenv.load_dotenv(env_path, verbose=True, override=True)
-    else:
-        raise FileNotFoundError(f'.env file not found at {env_path} ')
-
-    admin_config = AdminConfig()
-    admin_config.REBROADCAST_NIP89 = False
-    admin_config.UPDATE_PROFILE = False
-    dvm = build_example("Unstable Diffusion", "unstable_diffusion", admin_config, os.getenv("N_SERVER"), "stabilityai/stable-diffusion-xl", "")
-    dvm.run()
-
-    keep_alive()

nostr_dvm/tasks/imagegeneration_sdxlimg2img.py

@@ -198,6 +198,7 @@ class ImageGenerationSDXLIMG2IMG(DVMTaskInterface):
 # playground or elsewhere
 def build_example(name, identifier, admin_config, server_address, default_lora="", strength=0.6):
     dvm_config = build_default_config(identifier)
+    dvm_config.USE_OWN_VENV = False
     admin_config.LUD16 = dvm_config.LN_ADDRESS
 
     nip89info = {
@@ -233,18 +234,13 @@ def build_example(name, identifier, admin_config, server_address, default_lora="
                                       admin_config=admin_config, options=options)
 
 
+def process_venv():
+    args = DVMTaskInterface.process_args()
+    dvm_config = build_default_config(args.identifier)
+    dvm = ImageGenerationSDXLIMG2IMG(name="", dvm_config=dvm_config, nip89config=NIP89Config(), admin_config=None)
+    result = dvm.process(json.loads(args.request))
+    DVMTaskInterface.write_output(result, args.output)
+
+
 if __name__ == '__main__':
-    env_path = Path('.env')
+    process_venv()
-    if env_path.is_file():
-        print(f'loading environment from {env_path.resolve()}')
-        dotenv.load_dotenv(env_path, verbose=True, override=True)
-    else:
-        raise FileNotFoundError(f'.env file not found at {env_path} ')
-
-    admin_config = AdminConfig()
-    admin_config.REBROADCAST_NIP89 = False
-    admin_config.UPDATE_PROFILE = False
-    dvm = build_example("Image Converter Inkpunk", "image2image", admin_config, os.getenv("N_SERVER"), "", 0.6)
-    dvm.run()
-
-    keep_alive()

nostr_dvm/tasks/imageinterrogator.py

@@ -113,6 +113,7 @@ class ImageInterrogator(DVMTaskInterface):
 # playground or elsewhere
 def build_example(name, identifier, admin_config, server_address):
     dvm_config = build_default_config(identifier)
+    dvm_config.USE_OWN_VENV = False
     admin_config.LUD16 = dvm_config.LN_ADDRESS
 
     nip89info = {
@@ -144,18 +145,13 @@ def build_example(name, identifier, admin_config, server_address):
                                       admin_config=admin_config, options=options)
 
 
+def process_venv():
+    args = DVMTaskInterface.process_args()
+    dvm_config = build_default_config(args.identifier)
+    dvm = ImageInterrogator(name="", dvm_config=dvm_config, nip89config=NIP89Config(), admin_config=None)
+    result = dvm.process(json.loads(args.request))
+    DVMTaskInterface.write_output(result, args.output)
+
+
 if __name__ == '__main__':
-    env_path = Path('.env')
+    process_venv()
-    if env_path.is_file():
-        print(f'loading environment from {env_path.resolve()}')
-        dotenv.load_dotenv(env_path, verbose=True, override=True)
-    else:
-        raise FileNotFoundError(f'.env file not found at {env_path} ')
-
-    admin_config = AdminConfig()
-    admin_config.REBROADCAST_NIP89 = False
-    admin_config.UPDATE_PROFILE = False
-    dvm = build_example("Image Interrogator", "imageinterrogator", admin_config, os.getenv("N_SERVER"))
-    dvm.run()
-
-    keep_alive()

nostr_dvm/tasks/imageupscale.py

@@ -65,13 +65,11 @@ class ImageUpscale(DVMTaskInterface):
                 if tag.as_vec()[1] == "upscale":
                     out_scale = tag.as_vec()[2]
 
-
-
         io_input_image = {
-        "id": "input_image",
+            "id": "input_image",
-        "type": "input",
+            "type": "input",
-        "src": "url:Image",
+            "src": "url:Image",
-        "uri": url
+            "uri": url
         }
 
         io_output = {
@@ -106,11 +104,13 @@ class ImageUpscale(DVMTaskInterface):
         except Exception as e:
             raise Exception(e)
 
+
 # We build an example here that we can call by either calling this file directly from the main directory,
 # or by adding it to our playground. You can call the example and adjust it to your needs or redefine it in the
 # playground or elsewhere
 def build_example(name, identifier, admin_config, server_address):
     dvm_config = build_default_config(identifier)
+    dvm_config.USE_OWN_VENV = False
     admin_config.LUD16 = dvm_config.LN_ADDRESS
 
     # A module might have options it can be initialized with, here we set a default model, lora and the server
@@ -134,21 +134,16 @@ def build_example(name, identifier, admin_config, server_address):
     nip89config.CONTENT = json.dumps(nip89info)
 
     return ImageUpscale(name=name, dvm_config=dvm_config, nip89config=nip89config,
-                                      admin_config=admin_config, options=options)
+                        admin_config=admin_config, options=options)
+
+
+def process_venv():
+    args = DVMTaskInterface.process_args()
+    dvm_config = build_default_config(args.identifier)
+    dvm = ImageUpscale(name="", dvm_config=dvm_config, nip89config=NIP89Config(), admin_config=None)
+    result = dvm.process(json.loads(args.request))
+    DVMTaskInterface.write_output(result, args.output)
 
 
 if __name__ == '__main__':
-    env_path = Path('.env')
+    process_venv()
-    if env_path.is_file():
-        print(f'loading environment from {env_path.resolve()}')
-        dotenv.load_dotenv(env_path, verbose=True, override=True)
-    else:
-        raise FileNotFoundError(f'.env file not found at {env_path} ')
-
-    admin_config = AdminConfig()
-    admin_config.REBROADCAST_NIP89 = False
-    admin_config.UPDATE_PROFILE = False
-    dvm = build_example("Image Upscaler", "imageupscale", admin_config, os.getenv("N_SERVER"))
-    dvm.run()
-
-    keep_alive()

nostr_dvm/tasks/textextraction_whisperx.py

@@ -154,6 +154,7 @@ class SpeechToTextWhisperX(DVMTaskInterface):
 # playground or elsewhere
 def build_example(name, identifier, admin_config, server_address):
     dvm_config = build_default_config(identifier)
+    dvm_config.USE_OWN_VENV = False
     admin_config.LUD16 = dvm_config.LN_ADDRESS
 
     # A module might have options it can be initialized with, here we set a default model, and the server
@@ -186,18 +187,12 @@ def build_example(name, identifier, admin_config, server_address):
                                 admin_config=admin_config, options=options)
 
 
+def process_venv():
+    args = DVMTaskInterface.process_args()
+    dvm_config = build_default_config(args.identifier)
+    dvm = SpeechToTextWhisperX(name="", dvm_config=dvm_config, nip89config=NIP89Config(), admin_config=None)
+    result = dvm.process(json.loads(args.request))
+    DVMTaskInterface.write_output(result, args.output)
+
 if __name__ == '__main__':
-    env_path = Path('.env')
+    process_venv()
-    if env_path.is_file():
-        print(f'loading environment from {env_path.resolve()}')
-        dotenv.load_dotenv(env_path, verbose=True, override=True)
-    else:
-        raise FileNotFoundError(f'.env file not found at {env_path} ')
-
-    admin_config = AdminConfig()
-    admin_config.REBROADCAST_NIP89 = False
-    admin_config.UPDATE_PROFILE = False
-    dvm = build_example("Whisperer", "whisperx", admin_config, os.getenv("N_SERVER"))
-    dvm.run()
-
-    keep_alive()

setup.py

@@ -13,10 +13,7 @@ setup(
     author_email="believethehypeonnostr@proton.me",
     description=DESCRIPTION,
     long_description=LONG_DESCRIPTION,
-    packages=find_packages(include=['nostr_dvm', 'nostr_dvm.interfaces', 'nostr_dvm.tasks',
+    packages=find_packages(include=['nostr_dvm/**']),
-                                    'nostr_dvm.utils', 'nostr_dvm.utils.scrapper',
-                                    'nostr_dvm.backends', 'nostr_dvm.backends.mlx',
-                                    'nostr_dvm.backends.mlx.stablediffusion']),
     install_requires=["nostr-sdk==0.0.5",
                       "bech32==1.2.0",
                       "pycryptodome==3.19.0",