option to use venv or not per module, added tts

nostr_dvm/tasks/texttospeech.py

@@ -0,0 +1,136 @@
+import json
+import os
+os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
+from pathlib import Path
+
+from nostr_dvm.interfaces.dvmtaskinterface import DVMTaskInterface
+from nostr_dvm.utils.admin_utils import AdminConfig
+from nostr_dvm.utils.definitions import EventDefinitions
+from nostr_dvm.utils.dvmconfig import DVMConfig, build_default_config
+from nostr_dvm.utils.nip89_utils import NIP89Config, check_and_set_d_tag
+from nostr_dvm.utils.output_utils import upload_media_to_hoster
+
+"""
+This File contains a Module to generate Audio based on an input and a voice
+
+Accepted Inputs: Text
+Outputs: Generated Audiofile
+"""
+
+
+class TextToSpeech(DVMTaskInterface):
+    KIND: int = EventDefinitions.KIND_NIP90_TEXT_TO_SPEECH
+    TASK: str = "text-to-speech"
+    FIX_COST: float = 0
+    dependencies = [("nostr-dvm", "nostr-dvm"),
+                    ("TTS", "TTS==0.22.0")]
+
+    def __init__(self, name, dvm_config: DVMConfig, nip89config: NIP89Config,
+                 admin_config: AdminConfig = None, options=None):
+        dvm_config.SCRIPT = os.path.abspath(__file__)
+        super().__init__(name, dvm_config, nip89config, admin_config, options)
+
+    def is_input_supported(self, tags):
+        for tag in tags:
+            if tag.as_vec()[0] == 'i':
+                input_value = tag.as_vec()[1]
+                input_type = tag.as_vec()[2]
+                if input_type != "text":
+                    return False
+
+        return True
+
+    def create_request_from_nostr_event(self, event, client=None, dvm_config=None):
+        request_form = {"jobID": event.id().to_hex() + "_" + self.NAME.replace(" ", "")}
+        prompt = "test"
+        if self.options.get("input_file") and self.options.get("input_file") != "":
+            input_file = self.options['input_file']
+        else:
+            input_file = "https://media.nostr.build/av/de104e3260be636533a56fd4468b905c1eb22b226143a997aa936b011122af8a.wav"
+            import urllib.request
+            if not Path.exists(Path(r'cache/input.wav')):
+                urllib.request.urlretrieve(input_file, "cache/input.wav")
+        language = "en"
+
+        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]
+                if input_type == "url":
+                    input_file = tag.as_vec()[1]
+            elif tag.as_vec()[0] == 'param':
+                param = tag.as_vec()[1]
+                if param == "language":  # check for param type
+                    language = tag.as_vec()[2]
+
+        options = {
+            "prompt": prompt,
+            "input_wav": input_file,
+            "language": language
+        }
+        request_form['options'] = json.dumps(options)
+
+        return request_form
+
+    def process(self, request_form):
+        import torch
+        from TTS.api import TTS
+        options = DVMTaskInterface.set_options(request_form)
+        device = "cuda" if torch.cuda.is_available() else "cpu"
+            #else "mps" if torch.backends.mps.is_available() \
+
+        print(TTS().list_models())
+        try:
+            tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to(device)
+
+            tts.tts_to_file(
+                text=options["prompt"],
+                speaker_wav="cache/input.wav", language=options["language"], file_path="outputs/output.wav")
+            result = upload_media_to_hoster("outputs/output.wav")
+            return result
+        except Exception as e:
+            print("Error in Module: " + str(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):
+    dvm_config = build_default_config(identifier)
+    admin_config.LUD16 = dvm_config.LN_ADDRESS
+
+    options = {'input_file': ""}
+
+    nip89info = {
+        "name": name,
+        "image": "https://image.nostr.build/c33ca6fc4cc038ca4adb46fdfdfda34951656f87ee364ef59095bae1495ce669.jpg",
+        "about": "I Generate Speech from Text",
+        "encryptionSupported": True,
+        "cashuAccepted": True,
+        "nip90Params": {
+            "language": {
+                "required": False,
+                "values": []
+            }
+        }
+    }
+
+    nip89config = NIP89Config()
+    nip89config.DTAG = check_and_set_d_tag(identifier, name, dvm_config.PRIVATE_KEY, nip89info["image"])
+    nip89config.CONTENT = json.dumps(nip89info)
+
+    return TextToSpeech(name=name, dvm_config=dvm_config, nip89config=nip89config, admin_config=admin_config,
+                        options=options)
+
+
+def process_venv():
+    args = DVMTaskInterface.process_args()
+    dvm_config = build_default_config(args.identifier)
+    dvm = TextToSpeech(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__':
+    process_venv()