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from typing import Optional
import gradio as gr
from huggingface_hub import HfApi
from .config import RUN_LOCALLY
from .hf_utils import extract_quantization, get_gguf_files_from_repo, extract_username
from .processing import process_split_request
def load_gguf_files(
source_repo_id: str, oauth_token: Optional[gr.OAuthToken]
) -> gr.Dropdown:
"""Load GGUF files from selected repository"""
if not source_repo_id:
return gr.Dropdown(choices=[], value=None, interactive=False)
try:
if RUN_LOCALLY:
api = HfApi()
else:
token = oauth_token.token if oauth_token else None
api = HfApi(token=token)
gguf_files = get_gguf_files_from_repo(source_repo_id, api)
if not gguf_files:
return gr.Dropdown(
choices=["No GGUF files found in this repository"],
value=None,
interactive=True,
)
return gr.Dropdown(
choices=gguf_files,
value=gguf_files[0] if gguf_files else None,
interactive=True,
)
except Exception as e:
return gr.Dropdown(choices=[f"Error: {str(e)}"], value=None, interactive=True)
def create_ui() -> gr.Blocks:
"""Create and return the Gradio UI"""
with gr.Blocks() as demo:
gr.Markdown(
value="# GGUF Splitter",
elem_classes=["main-header"],
)
if not RUN_LOCALLY:
with gr.Group():
login_message = gr.Markdown(
value="### Connect your Hugging Face account to split and upload GGUF models.\n\nDue to platform storage limitations, split files must be uploaded directly to your account after processing - they cannot be stored for later download.",
elem_classes=["login-message"]
)
login_btn = gr.LoginButton(size="lg")
else:
login_message = gr.Markdown(visible=False)
login_btn = None
gr.Markdown("### Step 1: Select Source Model")
with gr.Group():
repo_selector = gr.Textbox(
label="Model Repository",
placeholder="Enter a Hugging Face model ID (e.g., Qwen/Qwen3-0.6B-GGUF)",
info="Enter the full repository ID from Hugging Face",
)
load_files_btn = gr.Button("Load GGUF Files", variant="secondary")
gguf_selector = gr.Dropdown(
label="GGUF File",
choices=[],
value=None,
interactive=False,
info="Select the GGUF file you want to split into shards",
)
gr.Markdown("### Step 2: Configure Output")
with gr.Group():
if not RUN_LOCALLY:
repo_name = gr.Textbox(
label="Target Repository Name",
info="The sharded model will be uploaded to this repository",
interactive=False,
)
with gr.Row():
public_toggle = gr.Checkbox(
label="Public Repository",
value=True,
info="Uncheck to create a private repository",
interactive=False,
scale=1,
)
else:
repo_name = gr.Textbox(
visible=False,
interactive=False,
)
public_toggle = gr.Checkbox(
visible=False,
interactive=False,
)
gr.Markdown("### Step 3: Split & " + ("Upload" if not RUN_LOCALLY else "Save"))
process_btn = gr.Button(
"Split and " + ("Upload GGUF" if not RUN_LOCALLY else "Save GGUF"),
variant="primary",
interactive=False,
size="lg",
elem_classes=["action-btn"],
)
with gr.Accordion("Output Log", open=True):
output_display = gr.Markdown(
value="*Waiting for action...*", elem_classes=["status-box"]
)
def update_components_on_login(
profile: Optional[gr.OAuthProfile], oauth_token: Optional[gr.OAuthToken]
) -> dict:
"""Update component visibility and interactivity based on login state"""
if profile and oauth_token:
return {
login_message: gr.Markdown(visible=False),
repo_selector: gr.Textbox(interactive=True),
load_files_btn: gr.Button(interactive=True),
repo_name: gr.Textbox(interactive=True),
gguf_selector: gr.Dropdown(interactive=True),
public_toggle: gr.Checkbox(interactive=True),
process_btn: gr.Button(interactive=True),
}
else:
return {
login_message: gr.Markdown(visible=True),
repo_selector: gr.Textbox(interactive=False),
load_files_btn: gr.Button(interactive=False),
repo_name: gr.Textbox(interactive=False),
gguf_selector: gr.Dropdown(interactive=False),
public_toggle: gr.Checkbox(interactive=False),
process_btn: gr.Button(interactive=False),
}
if login_btn is not None:
demo.load(
fn=update_components_on_login,
inputs=[],
outputs=[
login_message,
repo_selector,
load_files_btn,
repo_name,
gguf_selector,
public_toggle,
process_btn,
],
)
else:
demo.load(
fn=lambda: {
login_message: gr.Markdown(visible=False),
repo_selector: gr.Textbox(interactive=True),
load_files_btn: gr.Button(interactive=True),
repo_name: gr.Textbox(interactive=True),
gguf_selector: gr.Dropdown(interactive=True),
public_toggle: gr.Checkbox(interactive=True),
process_btn: gr.Button(interactive=True),
},
outputs=[
login_message,
repo_selector,
load_files_btn,
repo_name,
gguf_selector,
public_toggle,
process_btn,
],
)
def on_repo_selected(repo_id: str, oauth_token: Optional[gr.OAuthToken]):
"""Load GGUF files when a repository is selected"""
return load_gguf_files(repo_id, oauth_token)
def update_repo_name_on_selection(
source_repo_id: str,
gguf_filename: str,
oauth_token: Optional[gr.OAuthToken],
):
"""Update repository name based on selected source repo and GGUF file"""
if not source_repo_id or not gguf_filename:
return gr.Textbox(value="")
if not oauth_token:
return gr.Textbox(
value="", info="Sign in to auto-generate repository name"
)
try:
api = HfApi(token=oauth_token.token)
user_info = api.whoami()
username = extract_username(user_info)
if not username:
return gr.Textbox(
value="", info="Unable to determine your Hugging Face username"
)
model_name = source_repo_id.split("/")[-1]
model_name = re.sub(r"-?GGUF$", "", model_name, flags=re.IGNORECASE)
quantization = extract_quantization(gguf_filename)
suffix = f"gguf-sharded-{quantization}-{model_name}"
default_name = f"{username}/{suffix}"
return gr.Textbox(value=default_name)
except Exception:
return gr.Textbox(
value="", info="Unable to auto-generate repository name"
)
load_files_btn.click(
fn=on_repo_selected, inputs=[repo_selector], outputs=gguf_selector
)
gguf_selector.change(
fn=update_repo_name_on_selection,
inputs=[repo_selector, gguf_selector],
outputs=repo_name,
)
process_btn.click(
fn=process_split_request,
inputs=[
repo_name,
repo_selector,
gguf_selector,
public_toggle,
output_display,
],
outputs=output_display,
)
return demo
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