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app.py

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+
+import gradio as gr
+import fitz  # PyMuPDF
+import openai
+import os
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+def extract_text_from_pdf(pdf_file):
+    with fitz.open("pdf", pdf_file.read()) as doc:
+        return "".join([page.get_text() for page in doc])
+
+def clean_text(text):
+    text = text.replace("\n", " ").replace("  ", " ")
+    return text.strip()
+
+def split_text(text, max_tokens=1500):
+    words = text.split()
+    return [" ".join(words[i:i + max_tokens]) for i in range(0, len(words), max_tokens)]
+
+def summarize_chunk(chunk, prompt):
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {"role": "system", "content": prompt},
+            {"role": "user", "content": chunk}
+        ],
+        temperature=0.5,
+        max_tokens=500
+    )
+    return response.choices[0].message["content"].strip()
+
+def summarize_paper(file):
+    text = extract_text_from_pdf(file)
+    cleaned_text = clean_text(text)
+    chunks = split_text(cleaned_text)
+
+    full_summary = ""
+    for chunk in chunks:
+        summary = summarize_chunk(chunk, "Summarize this academic research paper for a general audience:")
+        full_summary += summary + "\n\n"
+
+    elim5 = summarize_chunk(cleaned_text, "Explain this paper to a 10-year-old in simple terms:")
+    why_matters = summarize_chunk(cleaned_text, "Why does this research matter? Explain its significance.")
+    tldr = summarize_chunk(cleaned_text, "Give a 1-line TL;DR summary of this paper.")
+
+    return full_summary, elim5, why_matters, tldr
+
+with gr.Blocks() as demo:
+    gr.Markdown("📄 **Paper News Summarizer** — Upload a research paper PDF and get a human-friendly summary, ELI5, and TL;DR. Powered by GPT-3.5.")
+    with gr.Row():
+        with gr.Column(scale=1):
+            file_input = gr.File(label="Upload Research Paper (PDF)", file_types=[".pdf"])
+            clear_btn = gr.Button("Clear")
+            submit_btn = gr.Button("Submit")
+        with gr.Column(scale=2):
+            summary_output = gr.Textbox(label="📘 Full Summary", lines=10, show_copy_button=True)
+            elim5_output = gr.Textbox(label="🧒 ELI5 Summary", lines=2, show_copy_button=True)
+            why_output = gr.Textbox(label="🎯 Why It Matters", lines=2, show_copy_button=True)
+            tldr_output = gr.Textbox(label="⚡ TL;DR", lines=2, show_copy_button=True)
+
+    def process(file):
+        return summarize_paper(file)
+
+    submit_btn.click(fn=process, inputs=file_input, outputs=[summary_output, elim5_output, why_output, tldr_output])
+    clear_btn.click(fn=lambda: ("", "", "", ""), inputs=[], outputs=[summary_output, elim5_output, why_output, tldr_output])
+
+demo.launch()

requirements.txt

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+
+openai==1.3.5
+PyMuPDF==1.22.0
+gradio==4.18.0