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import gradio as gr
from huggingface_hub import HfApi
import os
api = HfApi()
def list_models(search_query):
models = api.list_models(search=search_query, limit=10)
return [model.modelId for model in models]
def list_datasets(search_query):
datasets = api.list_datasets(search=search_query, limit=10)
return [dataset.id for dataset in datasets]
def download_model(model_id):
try:
api.snapshot_download(repo_id=model_id, repo_type="model")
return f"Modell {model_id} erfolgreich heruntergeladen."
except Exception as e:
return f"Fehler beim Herunterladen des Modells {model_id}: {str(e)}"
def download_dataset(dataset_id):
try:
api.snapshot_download(repo_id=dataset_id, repo_type="dataset")
return f"Dataset {dataset_id} erfolgreich heruntergeladen."
except Exception as e:
return f"Fehler beim Herunterladen des Datasets {dataset_id}: {str(e)}"
with gr.Blocks() as demo:
gr.Markdown("# Modell- und Dataset-Manager")
with gr.Tab("Modelle"):
model_search = gr.Textbox(label="Modell-Suche")
model_list = gr.Dropdown(label="Verfügbare Modelle")
model_search_btn = gr.Button("Modelle suchen")
model_download_btn = gr.Button("Ausgewähltes Modell herunterladen")
model_output = gr.Textbox(label="Ausgabe")
model_search_btn.click(list_models, inputs=model_search, outputs=model_list)
model_download_btn.click(download_model, inputs=model_list, outputs=model_output)
with gr.Tab("Datasets"):
dataset_search = gr.Textbox(label="Dataset-Suche")
dataset_list = gr.Dropdown(label="Verfügbare Datasets")
dataset_search_btn = gr.Button("Datasets suchen")
dataset_download_btn = gr.Button("Ausgewähltes Dataset herunterladen")
dataset_output = gr.Textbox(label="Ausgabe")
dataset_search_btn.click(list_datasets, inputs=dataset_search, outputs=dataset_list)
dataset_download_btn.click(download_dataset, inputs=dataset_list, outputs=dataset_output)
demo.launch()
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