Update inference_gradio.py

inference_gradio.py

@@ -12,6 +12,8 @@ import torchaudio
 import soundfile as sf
 from pathlib import Path
 
+from cached_path import cached_path
+
 from lemas_tts.api import TTS, PRETRAINED_ROOT, CKPTS_ROOT
 
 # Global variables
@@ -33,6 +35,9 @@ device = (
 
 REPO_ROOT = Path(__file__).resolve().parent
 
+# HF location for large TTS checkpoints (too big for Space storage)
+HF_PRETRAINED_ROOT = "hf://LEMAS-Project/LEMAS-TTS/pretrained_models"
+
 # 1) 指向 `pretrained_models` 里的 libespeak-ng.so（本地路径）
 ESPEAK_LIB = Path(PRETRAINED_ROOT) / "espeak-ng-lib" / "libespeak-ng.so"
 os.environ["PHONEMIZER_ESPEAK_LIBRARY"] = str(ESPEAK_LIB)
@@ -117,6 +122,11 @@ def cancel_denoise(audio_info):
 def get_checkpoints_project(project_name=None, is_gradio=True):
     """Get available checkpoint files"""
     checkpoint_dir = [str(CKPTS_ROOT)]
+    # Remote ckpt locations on HF (used when local ckpts are not present)
+    remote_ckpts = {
+        "multilingual_grl": f"{HF_PRETRAINED_ROOT}/ckpts/multilingual_grl/multilingual_grl.safetensors",
+        "multilingual_prosody": f"{HF_PRETRAINED_ROOT}/ckpts/multilingual_prosody/multilingual_prosody.safetensors",
+    }
 
     if project_name is None:
         # Look for checkpoints in local directory
@@ -126,12 +136,17 @@ def get_checkpoints_project(project_name=None, is_gradio=True):
                 files_checkpoints.extend(glob(os.path.join(path, "**/*.pt"), recursive=True))
                 files_checkpoints.extend(glob(os.path.join(path, "**/*.safetensors"), recursive=True))
                 break
+        # Fallback to remote ckpts if none found locally
+        if not files_checkpoints:
+            files_checkpoints = list(remote_ckpts.values())
     else:
         if os.path.isdir(checkpoint_dir[0]):
             files_checkpoints = glob(os.path.join(checkpoint_dir[0], project_name, "*.pt"))
             files_checkpoints.extend(glob(os.path.join(checkpoint_dir[0], project_name, "*.safetensors")))
         else:
-            files_checkpoints = []
+            # No local ckpts for this project, try remote mapping
+            ckpt = remote_ckpts.get(project_name)
+            files_checkpoints = [ckpt] if ckpt is not None else []
     print("files_checkpoints:", project_name, files_checkpoints)
     # Separate pretrained and regular checkpoints
     pretrained_checkpoints = [f for f in files_checkpoints if "pretrained_" in os.path.basename(f)]
@@ -188,9 +203,16 @@ def infer(
 ):
     global last_checkpoint, last_device, tts_api, last_ema
 
-    # Resolve checkpoint path (local or HF-style, though we now rely on local PRETRAINED_ROOT)
+    # Resolve checkpoint path (local or HF URL)
     ckpt_path = file_checkpoint
-    ckpt_resolved = ckpt_path
+    if isinstance(ckpt_path, str) and ckpt_path.startswith("hf://"):
+        try:
+            ckpt_resolved = str(cached_path(ckpt_path))
+        except Exception as e:
+            traceback.print_exc()
+            return None, f"Error downloading checkpoint: {str(e)}", ""
+    else:
+        ckpt_resolved = ckpt_path
 
     if not os.path.isfile(ckpt_resolved):
         return None, "Checkpoint not found!", ""