Don't forget to mount mean character embeddings and add security impr…

…ovements

code/app.py

@@ -18,15 +18,15 @@
 # Load speaker embeddings and gpt cond latents into memory for performance (~100mb)
 CHARACTER_SPEAKER_EMBEDDINGS = {}
 CHARACTER_GPT_COND_LATENTS = {}
-for file in Path("mean_character_embeddings").glob("*_speaker_embedding.pt"):
+for file in Path(settings.MEAN_CHARACTER_EMBEDDINGS_PATH).glob("*_speaker_embedding.pt"):
     character = file.stem[:-18]
 
     CHARACTER_SPEAKER_EMBEDDINGS[character] = torch.load(
-        f"mean_character_embeddings/{character}_speaker_embedding.pt",
+        f"{settings.MEAN_CHARACTER_EMBEDDINGS_PATH}/{character}_speaker_embedding.pt",
         map_location=torch.device(settings.DEVICE),
     )
     CHARACTER_GPT_COND_LATENTS[character] = torch.load(
-        f"mean_character_embeddings/{character}_gpt_cond_latent.pt",
+        f"{settings.MEAN_CHARACTER_EMBEDDINGS_PATH}/{character}_gpt_cond_latent.pt",
         map_location=torch.device(settings.DEVICE),
     )
     print(file)

code/settings.py

@@ -3,10 +3,12 @@
 
 import torch
 
+DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
+
 CHECKPOINT_DIR = "/xtts_model"
 CHECKPOINTS_CONFIG_JSON = "/xtts_model/config.json"
 CHECKPOINT_VOCAB_JSON = "/xtts_model/vocab.json"
-DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
+MEAN_CHARACTER_EMBEDDINGS_PATH = "/mean_character_embeddings"
 
 GRADIO_EXAMPLES_CACHE = os.environ["GRADIO_EXAMPLES_CACHE"]
 SECRET_KEY = os.environ["SECRET_KEY"]

docker-compose.example.yml

@@ -7,9 +7,14 @@ services:
       - "1337:1337"
     volumes:
       - ./current_model/:/xtts_model/:ro
+      - ./mean_character_embeddings/:/mean_character_embeddings/:ro
+    cap_drop:
+      - ALL
+    security_opt:
+      - no-new-privileges:true
     environment:
       GRADIO_EXAMPLES_CACHE: "/tmp/"
       GRADIO_ANALYTICS_ENABLED: False
       GRADIO_SERVER_NAME: "0.0.0.0"
       GRADIO_SERVER_PORT: 1337
-      SECRET_KEY: "changeme"
+      SECRET_KEY: "changeme"