Update config.json

config.json

@@ -1,4 +1,158 @@
 {
-  "name": "lemas-tts",
-  "type": "multilingual"
-}
+  "root": "pretrained_models",
+  "structure": {
+    "ckpts": {
+      "multilingual_grl": {
+        "path": "pretrained_models/ckpts/multilingual_grl",
+        "description": "Main LEMAS-TTS model (multilingual_grl)",
+        "files": [
+          {
+            "path": "pretrained_models/ckpts/multilingual_grl/multilingual_grl.safetensors",
+            "info": "Unconditional/text-conditioned non-autoregressive model weights with GRL, supporting multilingual TTS and editing (default Edit Model in Gradio)"
+          }
+        ]
+      },
+      "multilingual_prosody": {
+        "path": "pretrained_models/ckpts/multilingual_prosody",
+        "description": "non-autoregressive variant with an additional prosody encoder",
+        "files": [
+          {
+            "path": "pretrained_models/ckpts/multilingual_prosody/multilingual_prosody.safetensors",
+            "info": "Multilingual model weights with global prosody conditioning enabled (selectable in the model menu)"
+          }
+        ]
+      },
+      "prosody_encoder": {
+        "path": "pretrained_models/ckpts/prosody_encoder",
+        "description": "Pretssel / UnitY2-style prosody encoder used by the non-autoregressive prosody backend",
+        "files": [
+          {
+            "path": "pretrained_models/ckpts/prosody_encoder/pretssel_cfg.json",
+            "info": "Architecture configuration for the Pretssel/UnitY2 prosody encoder (dimensions, number of layers, etc.)"
+          },
+          {
+            "path": "pretrained_models/ckpts/prosody_encoder/prosody_encoder_UnitY2.pt",
+            "info": "Prosody encoder weights, used to extract global prosody embeddings from reference audio"
+          }
+        ]
+      },
+      "vocos-mel-24khz": {
+        "path": "pretrained_models/ckpts/vocos-mel-24khz",
+        "description": "Vocos neural vocoder (mel → 24kHz waveform)",
+        "files": [
+          {
+            "path": "pretrained_models/ckpts/vocos-mel-24khz/config.yaml",
+            "info": "Vocos vocoder configuration defining mel feature dimensions and network architecture"
+          },
+          {
+            "path": "pretrained_models/ckpts/vocos-mel-24khz/pytorch_model.bin",
+            "info": "Main Vocos vocoder weights, used to decode mel features in the CFM backend"
+          },
+          {
+            "path": "pretrained_models/ckpts/vocos-mel-24khz/README.md",
+            "info": "Documentation for the vocoder (origin, usage, and notes)"
+          }
+        ]
+      }
+    },
+    "data": {
+      "multilingual_grl": {
+        "path": "pretrained_models/data/multilingual_grl",
+        "description": "Text vocabulary for the multilingual_grl model",
+        "files": [
+          {
+            "path": "pretrained_models/data/multilingual_grl/vocab.txt",
+            "info": "phone vocabulary corresponding to the text embeddings of the multilingual_grl model"
+          }
+        ]
+      },
+      "multilingual_prosody": {
+        "path": "pretrained_models/data/multilingual_prosody",
+        "description": "Text vocabulary for the multilingual_prosody model",
+        "files": [
+          {
+            "path": "pretrained_models/data/multilingual_prosody/vocab.txt",
+            "info": "Shared text vocabulary used by the multilingual_prosody model"
+          }
+        ]
+      }
+    },
+    "demos": {
+      "root": "pretrained_models/demos",
+      "files": [
+        {
+          "path": "pretrained_models/demos/test.wav",
+          "info": "Simple test audio used for quick validation of gradio script"
+        }
+      ],
+      "lemas_edit_test": {
+        "path": "pretrained_models/demos/lemas_edit_test",
+        "description": "Audio samples and alignment annotations for LEMAS-Edit demos",
+        "subdirs": {
+          "vocals": {
+            "path": "pretrained_models/demos/lemas_edit_test/vocals",
+            "files": [
+              {
+                "path": "pretrained_models/demos/lemas_edit_test/vocals/en_AUD0000000214_S0001522.mp3",
+                "info": "English demo audio used for AR/NAR editing examples"
+              },
+              {
+                "path": "pretrained_models/demos/lemas_edit_test/vocals/zh_emilia_zh_0008385782.mp3",
+                "info": "Chinese demo audio used for multilingual editing examples"
+              }
+            ]
+          },
+          "align": {
+            "path": "pretrained_models/demos/lemas_edit_test/align",
+            "files": [
+              {
+                "path": "pretrained_models/demos/lemas_edit_test/align/en_AUD0000000214_S0001522.json",
+                "info": "MMS alignment JSON for the English demo, including intervals, words, and modified_index used for editing"
+              },
+              {
+                "path": "pretrained_models/demos/lemas_edit_test/align/zh_emilia_zh_0008385782.json",
+                "info": "MMS alignment JSON for the Chinese demo"
+              }
+            ]
+          }
+        }
+      }
+    },
+    "uvr5": {
+      "path": "pretrained_models/uvr5",
+      "description": "Kim Vocal UVR5 models and configurations (used for denoising)",
+      "files": [
+        {
+          "path": "pretrained_models/uvr5/Kim_Vocal_1.onnx",
+          "info": "Main UVR5 model (ONNX format) for vocal/accompaniment separation and denoising"
+        },
+        {
+          "path": "pretrained_models/uvr5/MDX-Net-Kim-Vocal1.json",
+          "info": "UVR5 model architecture and inference configuration (channels, frame length, etc.)"
+        },
+        {
+          "path": "pretrained_models/uvr5/model_data.json",
+          "info": "UVR5 metadata including presets, model list, and default parameters"
+        },
+        {
+          "path": "pretrained_models/uvr5/model_name_mapper.json",
+          "info": "Mapping from internal UVR5 model names to human-readable names for frontend selection"
+        }
+      ]
+    },
+    "whisperx": {
+      "path": "pretrained_models/whisperx",
+      "description": "WhisperX VAD and segmentation model assets",
+      "files": [
+        {
+          "path": "pretrained_models/whisperx/whisperx-vad-segmentation.bin",
+          "info": "WhisperX voice activity detection (VAD) weights used for long-audio segmentation and ASR alignment assistance"
+        },
+        {
+          "path": "pretrained_models/whisperx/whisperx-vad-segmentation.bak",
+          "info": "Backup or legacy version of the VAD model, kept for safety"
+        }
+      ]
+    }
+  }
+}