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 = """
"""
# 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("") # 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("") # 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("") # 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()