Spaces:
Running
Running
import gradio as gr | |
import requests | |
from urllib.parse import urlparse, urljoin | |
from bs4 import BeautifulSoup | |
import asyncio | |
# HTML and JavaScript for the "Copy Code" button | |
copy_button_html = """ | |
<script> | |
function copyCode(textareaId) { | |
const text = document.querySelector(`#${textareaId} textarea`).value; | |
navigator.clipboard.writeText(text).then(() => { | |
alert("Text copied to clipboard!"); | |
}).catch(() => { | |
alert("Failed to copy text."); | |
}); | |
} | |
</script> | |
""" | |
# Common functions | |
def is_valid_url(url): | |
"""Checks if the string is a valid URL.""" | |
try: | |
result = urlparse(url) | |
return all([result.scheme, result.netloc]) # Check for scheme and domain | |
except: | |
return False | |
async def fetch_file_content(url): | |
"""Fetches the content of a file (CSS, JS, etc.) from a URL.""" | |
try: | |
response = await asyncio.to_thread(requests.get, url, timeout=5) | |
response.raise_for_status() | |
return response.text | |
except: | |
return "Failed to fetch content." | |
# URL to Text Converter | |
async def extract_additional_resources(url): | |
"""Extracts links to CSS, JS, and images from HTML code.""" | |
try: | |
response = await asyncio.to_thread(requests.get, url, timeout=5) | |
response.raise_for_status() | |
# Check if the content is HTML | |
if 'text/html' in response.headers.get('Content-Type', ''): | |
soup = BeautifulSoup(response.text, "html.parser") | |
# Extract CSS links (limit to 5) | |
css_links = [urljoin(url, link["href"]) for link in soup.find_all("link", rel="stylesheet") if "href" in link.attrs][:5] | |
# Extract JS links (limit to 5) | |
js_links = [urljoin(url, script["src"]) for script in soup.find_all("script") if "src" in script.attrs][:5] | |
# Extract image links (limit to 5) | |
img_links = [urljoin(url, img["src"]) for img in soup.find_all("img") if "src" in img.attrs][:5] | |
# Fetch CSS and JS content asynchronously | |
css_content = await asyncio.gather(*[fetch_file_content(link) for link in css_links]) | |
js_content = await asyncio.gather(*[fetch_file_content(link) for link in js_links]) | |
return css_links, js_links, img_links, css_content, js_content | |
else: | |
# If it's not HTML, treat it as a file | |
return [], [], [], [response.text], [] | |
except Exception as e: | |
return [], [], [], [], [] | |
async def convert_to_text(url): | |
# Handle view-source: URLs | |
if url.startswith("view-source:"): | |
url = url[len("view-source:"):] | |
if not is_valid_url(url): | |
return "Error: Please enter a valid URL.", "", None, [], [], [], [], [] # Return error message and empty data | |
try: | |
# Set headers to mimic a browser request | |
headers = { | |
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36" | |
} | |
response = await asyncio.to_thread(requests.get, url, headers=headers, timeout=5) | |
response.raise_for_status() # Check for HTTP errors (e.g., 404, 500) | |
# Return results | |
status = f"Request status: {response.status_code}" | |
content_length = f"Content size: {len(response.text)} characters" | |
results = f"{status}\n{content_length}" | |
# Save text content to a file | |
file_path = "downloaded_content.txt" | |
with open(file_path, "w", encoding="utf-8") as file: | |
file.write(response.text) | |
# Extract additional resources | |
css_links, js_links, img_links, css_content, js_content = await extract_additional_resources(url) | |
return results, response.text, file_path, css_links, js_links, img_links, css_content, js_content | |
except requests.exceptions.RequestException as e: | |
return f"Error: {e}", "", None, [], [], [], [], [] # Return error message and empty data | |
# Model to Text Converter | |
async def fetch_model_info(model_url): | |
"""Fetches model description and installation instructions.""" | |
try: | |
if "huggingface.co" in model_url: | |
# Fetch model card from Hugging Face | |
response = await asyncio.to_thread(requests.get, model_url, timeout=5) | |
response.raise_for_status() | |
soup = BeautifulSoup(response.text, "html.parser") | |
# Extract model description | |
description = soup.find("div", {"class": "prose"}).get_text(strip=True) if soup.find("div", {"class": "prose"}) else "No description available." | |
# Generate installation instructions | |
model_name = model_url.split("/")[-1] | |
install_instructions = f"To install this model, run:\n```bash\npip install transformers\n```\nThen load the model in Python:\n```python\nfrom transformers import AutoModel, AutoTokenizer\nmodel = AutoModel.from_pretrained('{model_name}')\ntokenizer = AutoTokenizer.from_pretrained('{model_name}')\n```" | |
return description, install_instructions | |
elif "github.com" in model_url: | |
# Fetch README from GitHub | |
readme_url = f"{model_url}/raw/main/README.md" | |
response = await asyncio.to_thread(requests.get, readme_url, timeout=5) | |
response.raise_for_status() | |
# Extract description from README | |
description = response.text if response.text else "No description available." | |
# Generate installation instructions | |
install_instructions = f"To install this model, clone the repository:\n```bash\ngit clone {model_url}.git\ncd {model_url.split('/')[-1]}\n```" | |
return description, install_instructions | |
else: | |
return "Unsupported repository.", "" | |
except Exception as e: | |
return f"Error: {e}", "" | |
async def fetch_model_file_content(model_url, file_path): | |
"""Fetches the content of a file from a model repository (Hugging Face or GitHub).""" | |
try: | |
# Construct the full URL to the file | |
if "huggingface.co" in model_url: | |
# Убираем /blob/main/ из URL, если он есть | |
if "/blob/main/" in model_url: | |
model_url = model_url.replace("/blob/main/", "/") | |
# Hugging Face URL format: https://huggingface.co/{model}/raw/main/{file_path} | |
full_url = f"{model_url}/raw/main/{file_path}" | |
elif "github.com" in model_url: | |
# GitHub URL format: https://github.com/{user}/{repo}/raw/main/{file_path} | |
full_url = f"{model_url}/raw/main/{file_path}" | |
else: | |
return "Error: Unsupported repository." | |
# Fetch the file content | |
response = await asyncio.to_thread(requests.get, full_url, timeout=5) | |
response.raise_for_status() | |
return response.text | |
except Exception as e: | |
return f"Error: {e}" | |
# Space to Text Converter | |
async def fetch_space_file_content(space_url, file_path): | |
"""Fetches the content of a file from a Hugging Face Space.""" | |
try: | |
# Construct the full URL to the file | |
if "huggingface.co/spaces" in space_url: | |
# Hugging Face Spaces URL format: https://huggingface.co/spaces/{user}/{space}/raw/main/{file_path} | |
full_url = f"{space_url}/raw/main/{file_path}" | |
else: | |
return "Error: Unsupported repository. Please provide a Hugging Face Space URL." | |
# Fetch the file content | |
response = await asyncio.to_thread(requests.get, full_url, timeout=5) | |
response.raise_for_status() | |
return response.text | |
except Exception as e: | |
return f"Error: {e}" | |
# Create the Gradio interface | |
with gr.Blocks() as demo: | |
gr.HTML(copy_button_html) # Add the "Copy Code" script | |
with gr.Tabs(): | |
# Tab 1: URL to Text Converter | |
with gr.Tab("URL to Text Converter"): | |
gr.Markdown("## URL to Text Converter") | |
gr.Markdown("Enter a URL to fetch its text content and download it as a .txt file.") | |
with gr.Row(): | |
url_input = gr.Textbox(label="Enter URL", placeholder="https://example.com or view-source:https://example.com") | |
with gr.Row(): | |
results_output = gr.Textbox(label="Request Results", interactive=False) | |
text_output = gr.Textbox(label="Text Content", interactive=True, elem_id="output-text") | |
with gr.Row(): | |
gr.HTML("<button onclick='copyCode(\"output-text\")'>Copy Code</button>") # Add the "Copy Code" button | |
file_output = gr.File(label="Download File", visible=False) # Hidden file download component | |
submit_button = gr.Button("Fetch Content") | |
submit_button.click( | |
fn=convert_to_text, | |
inputs=url_input, | |
outputs=[ | |
results_output, text_output, file_output, | |
gr.Textbox(label="CSS Files"), gr.Textbox(label="JS Files"), gr.Textbox(label="Images"), | |
gr.Textbox(label="CSS Content"), gr.Textbox(label="JS Content") | |
] | |
) | |
# Add an Accordion to show/hide additional resources | |
with gr.Accordion("Show/Hide Additional Resources", open=False): | |
gr.Markdown("### CSS Files") | |
css_output = gr.Textbox(label="CSS Files", interactive=False) | |
gr.Markdown("### JS Files") | |
js_output = gr.Textbox(label="JS Files", interactive=False) | |
gr.Markdown("### Images") | |
img_output = gr.Textbox(label="Images", interactive=False) | |
gr.Markdown("### CSS Content") | |
css_content_output = gr.Textbox(label="CSS Content", interactive=True) | |
gr.Markdown("### JS Content") | |
js_content_output = gr.Textbox(label="JS Content", interactive=True) | |
# Tab 2: Model to Text Converter | |
with gr.Tab("Model to Text Converter"): | |
gr.Markdown("## Model to Text Converter") | |
gr.Markdown("Enter a link to a model on Hugging Face or GitHub, and specify the file path.") | |
with gr.Row(): | |
model_url_input = gr.Textbox(label="Model URL", placeholder="https://huggingface.co/... or https://github.com/...") | |
file_path_input = gr.Textbox(label="File Path", placeholder="e.g., config.json or README.md") | |
with gr.Row(): | |
model_description_output = gr.Textbox(label="Model Description", interactive=False) | |
install_instructions_output = gr.Textbox(label="Installation Instructions", interactive=False) | |
with gr.Row(): | |
model_content_output = gr.Textbox(label="File Content", interactive=True, elem_id="model-content-output") | |
with gr.Row(): | |
gr.HTML("<button onclick='copyCode(\"model-content-output\")'>Copy Code</button>") # Add the "Copy Code" button | |
submit_model_button = gr.Button("Fetch Model Info and File Content") | |
submit_model_button.click( | |
fn=fetch_model_info, | |
inputs=[model_url_input], | |
outputs=[model_description_output, install_instructions_output] | |
) | |
submit_model_button.click( | |
fn=fetch_model_file_content, | |
inputs=[model_url_input, file_path_input], | |
outputs=[model_content_output] | |
) | |
# Tab 3: Space to Text Converter | |
with gr.Tab("Space to Text Converter"): | |
gr.Markdown("## Space to Text Converter") | |
gr.Markdown("Enter a link to a Hugging Face Space and specify the file path to fetch its content.") | |
with gr.Row(): | |
space_url_input = gr.Textbox(label="Space URL", placeholder="https://huggingface.co/spaces/...") | |
space_file_path_input = gr.Textbox(label="File Path", placeholder="e.g., app.py or README.md") | |
with gr.Row(): | |
space_content_output = gr.Textbox(label="File Content", interactive=True, elem_id="space-content-output") | |
with gr.Row(): | |
gr.HTML("<button onclick='copyCode(\"space-content-output\")'>Copy Code</button>") # Add the "Copy Code" button | |
submit_space_button = gr.Button("Fetch File Content") | |
submit_space_button.click( | |
fn=fetch_space_file_content, | |
inputs=[space_url_input, space_file_path_input], | |
outputs=[space_content_output] | |
) | |
# Launch the interface | |
demo.launch() |