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import gradio as gr
from markitdown import MarkItDown
import google.generativeai as genai
import tempfile
import os
from pathlib import Path
# Initialize MarkItDown
md = MarkItDown()
# Configure Gemini AI
genai.configure(api_key=os.getenv('GEMINI_KEY'))
model = genai.GenerativeModel('gemini-2.0-flash-exp')
def process_with_markitdown(input_path):
"""Process file or URL with MarkItDown and return text content"""
try:
result = md.convert(input_path)
return result.text_content
except Exception as e:
return f"Error processing input: {str(e)}"
import tempfile
import os
import io
def save_uploaded_file(file):
"""Save uploaded file to temporary location and return path.
Handles only file uploads, not URLs."""
if file is None:
return None
try:
temp_dir = tempfile.gettempdir()
temp_filename = tempfile.mkstemp(dir=temp_dir, suffix=os.path.splitext(file.name)[1])[1]
# Crucial: Check for valid file-like object
if hasattr(file, 'read'):
with open(temp_filename, 'wb') as f:
try:
while True:
chunk = file.read(8192)
if not chunk:
break
f.write(chunk)
except Exception as e:
return f"Error during file write: {str(e)}"
elif hasattr(file, 'getvalue'): # In-memory file-like
with open(temp_filename, 'wb') as f:
try:
f.write(file.getvalue())
except Exception as e:
return f"Error during file write: {str(e)}"
else:
return "Error: Unsupported file type."
return temp_filename
except Exception as e:
return f"Error saving file: {str(e)}"
async def summarize_text(text):
"""Summarize the input text using Gemini AI"""
try:
prompt = f"""Please provide a concise summary of the following text. Focus on the main points and key takeaways:
{text}
Summary:"""
response = await model.generate_content_async(prompt)
return response.text
except Exception as e:
return f"Error generating summary: {str(e)}"
async def process_input(input_text, uploaded_file=None):
"""Main function to process either URL or uploaded file"""
try:
if uploaded_file is not None:
# Handle file upload
temp_path = save_uploaded_file(uploaded_file)
if temp_path.startswith('Error'):
return temp_path
text = process_with_markitdown(temp_path)
# Clean up temporary file
try:
os.remove(temp_path)
except:
pass
elif input_text.startswith(('http://', 'https://')):
# Handle URL
text = process_with_markitdown(input_text)
else:
# Handle direct text input
text = input_text
if text.startswith('Error'):
return text
# Generate summary using Gemini AI
summary = await summarize_text(text)
return summary
except Exception as e:
return f"Error processing input: {str(e)}"
def clear_inputs():
return ["", None, ""]
# Create Gradio interface with drag-and-drop
with gr.Blocks(theme=gr.themes.Soft()) as iface:
gr.Markdown(
"""
# Summarizeit
> Summarize any document!
Enter a URL, paste text, or drag & drop a file to get a summary.
"""
)
with gr.Row():
input_text = gr.Textbox(
label="Enter URL or text",
placeholder="Enter a URL or paste text here...",
scale=2
)
with gr.Row():
file_upload = gr.File(
label="Drop files here or click to upload",
file_types=[
".pdf", ".docx", ".xlsx", ".csv", ".txt", ".md",
".html", ".htm", ".xml", ".json"
],
file_count="single",
scale=2
)
with gr.Row():
submit_btn = gr.Button("Summarize", variant="primary")
clear_btn = gr.Button("Clear")
output_text = gr.Textbox(
label="Summary",
lines=10,
show_copy_button=True
)
# Set up event handlers
submit_btn.click(
fn=process_input,
inputs=[input_text, file_upload],
outputs=output_text
)
clear_btn.click(
fn=clear_inputs,
outputs=[input_text, file_upload, output_text]
)
# Add examples
gr.Examples(
examples=[
["https://h3manth.com"],
["https://www.youtube.com/watch?v=bSHp7WVpPgc"],
["https://en.wikipedia.org/wiki/Three-body_problem"]
],
inputs=input_text
)
if __name__ == "__main__":
iface.launch() |