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README.md

@@ -1,12 +1,13 @@
----
-title: Space Splitter
-emoji: 🏃
-colorFrom: indigo
-colorTo: gray
-sdk: gradio
-sdk_version: 5.22.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Space Splitter
+emoji: 🙄
+colorFrom: indigo
+colorTo: purple
+sdk: gradio
+sdk_version: 5.22.0
+app_file: app.py
+pinned: false
+license: mit
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,92 @@
+import spaces
+
+@spaces.GPU
+def dummy_gpu():
+    pass
+
+import gradio as gr
+from huggingface_hub import HfApi, snapshot_download
+from huggingface_hub.hf_api import RepoFile
+from typing import Union
+import tempfile
+import shutil
+from pathlib import Path
+import time
+
+def split_repo(repo_id: str, user_name: str, space_name: str, storage_name: str, storage_type: str, is_private: bool=True, threshold: int=10 * 1024 * 1024, hf_token: Union[str, None]="", progress=gr.Progress(track_tqdm=True)):
+    TEMP_DIR = tempfile.mkdtemp()
+    exist_ok = False
+    use_dupe_api = False
+    info_md = ""
+    dl_code = ""
+    space_id = f"{user_name}/{space_name}"
+    storage_id = f"{user_name}/{storage_name}"
+    try:
+        kwargs = {}
+        if hf_token: kwargs["token"] = hf_token
+        else: raise Exception("Token not found.")
+        api = HfApi()
+        if not exist_ok:
+            if api.repo_exists(repo_id=space_id, repo_type="space", **kwargs): raise Exception(f"{space_id} already exists.")
+            if api.repo_exists(repo_id=storage_id, repo_type=storage_type, **kwargs): raise Exception(f"{space_id} already exists.")
+        info = api.list_repo_tree(repo_id=repo_id, repo_type="space", recursive=True, **kwargs)
+        lfiles = []
+        sfiles = []
+        for i in info:
+            if not isinstance(i, RepoFile): continue
+            if i.lfs is not None and i.lfs.size > threshold: lfiles.append(i.path)
+            else: sfiles.append(i.path)
+        #print("Large files: ", lfiles)
+        #print("Small files: ", sfiles)
+        if len(lfiles) == 0: raise Exception("Large file not found.")
+        lfiles_str = "[" + ", ".join(['"' + s + '"' for s in lfiles]) + "]"
+        sv = api.get_space_variables(repo_id=repo_id, **kwargs)
+        sv = [{str(k): str(v)} for k, v in sv.items()] if sv and len(sv) > 0 else []
+        if api.repo_exists(repo_id=space_id, repo_type="space", **kwargs) and exist_ok: api.delete_repo(repo_id=space_id, repo_type="space", **kwargs)
+        if use_dupe_api:
+            api.duplicate_space(from_id=repo_id, to_id=space_id, exist_ok=exist_ok, private=is_private, hardware="cpu-basic", variables=sv, **kwargs)
+            time.sleep(10) # wait for finishing of space duplication
+            api.delete_files(repo_id=space_id, repo_type="space", delete_patterns=lfiles, **kwargs)
+        else:
+            snapshot_download(repo_id=repo_id, repo_type="space", ignore_patterns=lfiles, local_dir=TEMP_DIR, **kwargs)
+            api.create_repo(repo_id=space_id, repo_type="space", space_hardware="cpu-basic", space_variables=sv, space_sdk="gradio", exist_ok=exist_ok, private=is_private, **kwargs)
+            api.upload_folder(repo_id=space_id, repo_type="space", ignore_patterns=lfiles, folder_path=TEMP_DIR, path_in_repo=".", **kwargs)
+        snapshot_download(repo_id=repo_id, repo_type="space", allow_patterns=lfiles, local_dir=TEMP_DIR, **kwargs)
+        api.create_repo(repo_id=storage_id, repo_type=storage_type, exist_ok=exist_ok, private=is_private, **kwargs)
+        api.upload_folder(repo_id=storage_id, repo_type=storage_type, allow_patterns=lfiles, folder_path=TEMP_DIR, path_in_repo=".", **kwargs)
+        lfiles_str = "[" + ", ".join(['"' + s + '"' for s in lfiles]) + "]"
+        dl_code = f'from huggingface_hub import snapshot_download\nlarge_files = {lfiles_str}\nsnapshot_download(repo_id="{storage_id}", repo_type="{storage_type}", allow_patterns=large_files, local_dir=".")\n'
+        info_md = f'## Your new space URL: [{space_id}](https://hf.co/spaces/{space_id})<br>\n## Your new storage URL: [{storage_id}](https://hf.co/{storage_id if storage_type == "model" else "datasets/" + storage_id})'
+    except Exception as e:
+        print(e)
+        gr.Warning(f"Error: {e}")
+    finally:
+        if Path(TEMP_DIR).exists() and Path(TEMP_DIR).is_dir(): shutil.rmtree(TEMP_DIR)
+        return info_md, dl_code
+
+css = """
+.title { font-size: 3em; align-items: center; text-align: center; }
+.info { align-items: center; text-align: center; }
+.block.result { margin: 1em 0; padding: 1em; box-shadow: 0 0 3px 3px #664422, 0 0 3px 2px #664422 inset; border-radius: 6px; background: #665544; }
+.desc [src$='#float'] { float: right; margin: 20px; }
+"""
+
+with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css, delete_cache=(60, 3600)) as demo:
+    repo_id = gr.Textbox(label="Source repo ID", placeholder="levihsu/OOTDiffusion", value="")
+    with gr.Row(equal_height=True):
+        user_name = gr.Textbox(label="Your user name", value="")
+        space_name = gr.Textbox(label="Destination repo name", placeholder="OOTDiffusion", value="")
+        storage_name = gr.Textbox(label="Storage repo name", placeholder="OOTDiffusion-storage", value="")
+        storage_type = gr.Radio(label="Storage repo type", choices=["dataset", "model"], value="model")
+        with gr.Column():
+            hf_token = gr.Textbox(label="Your HF write token", placeholder="hf_...", value="")
+            gr.Markdown("Your token is available at [hf.co/settings/tokens](https://huggingface.co/settings/tokens).", elem_classes="info")
+        threshold = gr.Number(label="Size threshold (bytes)", value=10 * 1024 * 1024, minimum=1, maximum=5 * 1024 * 1024 * 1024, step=1)
+        is_private = gr.Checkbox(label="Private", value=True)
+    run_button = gr.Button("Submit", variant="primary")
+    dl_code = gr.Textbox(label="Code", value="", show_copy_button=True)
+    info_md = gr.Markdown("<br><br><br>", elem_classes="result")
+
+    run_button.click(split_repo, [repo_id, user_name, space_name, storage_name, storage_type, is_private, threshold, hf_token], [info_md, dl_code])
+
+demo.queue().launch(ssr_mode=False)

requirements.txt

@@ -0,0 +1 @@
+huggingface_hub