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import gradio as gr
import fitz # PyMuPDF
import openai
import os
# Load API key from Hugging Face secret
openai.api_key = os.getenv("OPENAI_API_KEY")
# Extract text from PDF
def extract_text_from_pdf(file):
text = ""
with fitz.open(stream=file.read(), filetype="pdf") as doc:
for page in doc:
text += page.get_text()
return text
# Split text into chunks
def split_text(text, max_tokens=1500):
import textwrap
return textwrap.wrap(text, max_tokens)
# Generate summary
def generate_summary(text):
chunks = split_text(text)
summaries = []
for i, chunk in enumerate(chunks):
print(f"⏳ Summarizing chunk {i + 1}/{len(chunks)}...")
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": f"Summarize the following:\n{chunk}"}],
temperature=0.5,
)
summaries.append(response['choices'][0]['message']['content'].strip())
return "\n\n".join(summaries)
# Generate all formats
def summarize_paper(pdf_file):
try:
raw_text = extract_text_from_pdf(pdf_file)
summary = generate_summary(raw_text)
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[
{"role": "user", "content": f"Make an ELI5 version of this:\n{summary}"}
],
temperature=0.7,
)
eli5 = response['choices'][0]['message']['content'].strip()
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[
{"role": "user", "content": f"Write a TL;DR of this:\n{summary}"}
],
temperature=0.7,
)
tldr = response['choices'][0]['message']['content'].strip()
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[
{"role": "user", "content": f"Why does this research matter? {summary}"}
],
temperature=0.7,
)
why_it_matters = response['choices'][0]['message']['content'].strip()
return summary, eli5, tldr, why_it_matters
except Exception as e:
return f"❌ Error: {str(e)}", "", "", ""
# Gradio Interface
with gr.Blocks() as demo:
gr.Markdown("📄 **Paper News Summarizer**\nUpload a research paper PDF and get a human-friendly summary, ELI5, TL;DR, and why it matters.")
with gr.Row():
pdf_file = gr.File(label="Upload Research Paper (PDF)", file_types=[".pdf"])
submit_btn = gr.Button("Submit")
clear_btn = gr.Button("Clear")
with gr.Row():
full_summary = gr.Textbox(label="📘 Full Summary", lines=10, interactive=False)
eli5_summary = gr.Textbox(label="🧒 ELI5", lines=5, interactive=False)
with gr.Row():
tldr_summary = gr.Textbox(label="⚡ TL;DR", lines=2, interactive=False)
importance = gr.Textbox(label="🎯 Why It Matters", lines=5, interactive=False)
submit_btn.click(summarize_paper, inputs=pdf_file, outputs=[full_summary, eli5_summary, tldr_summary, importance])
clear_btn.click(lambda: ("", "", "", ""), outputs=[full_summary, eli5_summary, tldr_summary, importance])
demo.launch()
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