Spaces:
Running
on
Zero
Running
on
Zero
import os | |
import gradio as gr | |
from repo_utils import extract_repo_content | |
def format_output(extracted_content, repo_url): | |
formatted_output = f"# Repository URL: {repo_url}\n\n" | |
for file_data in extracted_content: | |
if isinstance(file_data, dict) and 'header' in file_data: | |
formatted_output += f"### File: {file_data['header']['name']}\n" | |
formatted_output += f"**Type:** {file_data['header']['type']}\n" | |
formatted_output += f"**Size:** {file_data['header']['size']} bytes\n" | |
formatted_output += f"**Created:** {file_data['header']['creation_date']}\n" | |
formatted_output += f"**Modified:** {file_data['header']['modification_date']}\n" | |
formatted_output += "#### Content:\n" | |
formatted_output += f"```\n{file_data['content']}\n```\n\n" | |
else: | |
formatted_output += "Error in file data format.\n" | |
return formatted_output | |
def extract_and_display(url): | |
hf_token = os.getenv("HF_TOKEN") | |
hf_user = os.getenv("SPACE_AUTHOR_NAME") | |
if not hf_token or not hf_user: | |
return "Error: HF_TOKEN or SPACE_AUTHOR_NAME environment variable is not set." | |
extracted_content = extract_repo_content(url, hf_token, hf_user) | |
formatted_output = format_output(extracted_content, url) | |
return formatted_output | |
app = gr.Blocks(theme="sudeepshouche/minimalist") | |
with app: | |
gr.Markdown("# Hugging Face Space / Model Repository Content Extractor") | |
url_input = gr.Textbox(label="https:// URL of Repository", placeholder="Enter the repository URL here OR select an example below...") | |
url_examples = gr.Examples( | |
examples=[ | |
["https://huggingface.co/spaces/big-vision/paligemma-hf"], | |
["https://huggingface.co/google/paligemma-3b-mix-224"], | |
["https://huggingface.co/microsoft/Phi-3-vision-128k-instruct"], | |
["https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf"] | |
], | |
inputs=url_input | |
) | |
output_display = gr.Textbox(label="Extracted Repository Content", show_copy_button=True, lines=20, placeholder="Repository content will be extracted here...\n\nMetadata is captured for all files, but text content provided only for files less than 32 kb\n\n\n\nReview and search through the content here OR simply copy it for offline analysis!!. π€") | |
extract_button = gr.Button("Extract Content") | |
extract_button.click(fn=extract_and_display, inputs=url_input, outputs=output_display) | |
if __name__ == "__main__": | |
app.launch() | |