ENH: Skip download if model exists (#495)

xinference/model/llm/llm_family.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import datetime
 import logging
 import os
 import platform
@@ -450,15 +451,27 @@ def cache_from_modelscope(
 
     cache_dir = _get_cache_dir(llm_family, llm_spec)
     if llm_spec.model_format == "pytorch":
-        download_dir = snapshot_download(
-            llm_spec.model_id, revision=llm_spec.model_revision
+        meta_path = os.path.join(cache_dir, "__valid_download")
+        if os.path.exists(meta_path):
+            return cache_dir
+        download_dir = retry_download(
+            snapshot_download,
+            llm_family,
+            llm_spec,
+            llm_spec.model_id,
+            revision=llm_spec.model_revision,
         )
         for subdir, dirs, files in os.walk(download_dir):
             for file in files:
                 relpath = os.path.relpath(os.path.join(subdir, file), download_dir)
                 symlink_local_file(os.path.join(subdir, file), cache_dir, relpath)
+        with open(meta_path, "w") as f:
+            f.write(str(datetime.datetime.now()))
 
     elif llm_spec.model_format in ["ggmlv3", "ggufv2"]:
+        meta_path = os.path.join(cache_dir, f"__valid_download_{quantization}")
+        if os.path.exists(meta_path):
+            return cache_dir
         filename = llm_spec.model_file_name_template.format(quantization=quantization)
         download_path = retry_download(
             model_file_download,
@@ -469,6 +482,8 @@ def cache_from_modelscope(
             revision=llm_spec.model_revision,
         )
         symlink_local_file(download_path, cache_dir, filename)
+        with open(meta_path, "w") as f:
+            f.write(str(datetime.datetime.now()))
     else:
         raise ValueError(f"Unsupported format: {llm_spec.model_format}")
     return cache_dir
@@ -487,6 +502,9 @@ def cache_from_huggingface(
     cache_dir = _get_cache_dir(llm_family, llm_spec)
     if llm_spec.model_format == "pytorch":
         assert isinstance(llm_spec, PytorchLLMSpecV1)
+        meta_path = os.path.join(cache_dir, "__valid_download")
+        if os.path.exists(meta_path):
+            return cache_dir
 
         retry_download(
             huggingface_hub.snapshot_download,
@@ -497,9 +515,14 @@ def cache_from_huggingface(
             local_dir=cache_dir,
             local_dir_use_symlinks=True,
         )
+        with open(meta_path, "w") as f:
+            f.write(str(datetime.datetime.now()))
 
     elif llm_spec.model_format in ["ggmlv3", "ggufv2"]:
         assert isinstance(llm_spec, GgmlLLMSpecV1)
+        meta_path = os.path.join(cache_dir, f"__valid_download_{quantization}")
+        if os.path.exists(meta_path):
+            return cache_dir
         file_name = llm_spec.model_file_name_template.format(quantization=quantization)
         retry_download(
             huggingface_hub.hf_hub_download,
@@ -511,6 +534,8 @@ def cache_from_huggingface(
             local_dir=cache_dir,
             local_dir_use_symlinks=True,
         )
+        with open(meta_path, "w") as f:
+            f.write(str(datetime.datetime.now()))
     else:
         raise ValueError(f"Unsupported model format: {llm_spec.model_format}")