app.py

import gradio as gr
import fitz
import torch
from transformers import pipeline
import time, logging, re

logging.basicConfig(level=logging.ERROR)
device = -1  # CPU-only
print("⚠️ CPU-only. Expect ~20–30s for 300,000 chars.")

try:
    summarizer = pipeline("summarization", model="t5-small", device=device, torch_dtype=torch.float32)
except Exception as e:
    print(f"❌ Model loading failed: {str(e)}")
    exit(1)

def summarize_file(file_bytes):
    start = time.time()
    print(f"File type: {type(file_bytes)}")
    try:
        doc = fitz.open(stream=file_bytes, filetype="pdf")
        text = "".join(page.get_text("text") for page in doc)
        # Clean OCR noise: replace LaTeX, remove excessive whitespace, non-ASCII
        text = re.sub(r"\$\s*([^$]+)\s*\$", r"\1", text)  # Strip $...$
        text = re.sub(r"\\cap", "intersection", text)  # Handle ∩
        text = re.sub(r"\s+", " ", text).strip()  # Normalize whitespace
        text = "".join(c for c in text if ord(c) < 128)  # ASCII only
        print(f"Extracted chars: {len(text)}")
    except Exception as e:
        return f"❌ Text extraction failed: {str(e)}"
    if not text.strip(): return "❌ No text found"
    text = text[:300000]
    chunks = [text[i:i+2000] for i in range(0, len(text), 2000)]
    print(f"Chunks created: {len(chunks)}")
    if not chunks: return "❌ No chunks to summarize"
    summaries = []
    for i, chunk in enumerate(chunks):
        if time.time() - start > 20: 
            summaries.append("⚠️ Stopped early")
            break
        if sum(1 for c in chunk if not c.isalnum()) / len(chunk) > 0.5:  # Skip equation-heavy chunks
            summaries.append(f"**Chunk {i+1}**: Skipped (equation-heavy)")
            continue
        try:
            summary = summarizer(chunk, max_length=60, min_length=10, do_sample=False)[0]['summary_text']
            summaries.append(f"**Chunk {i+1}**:\n{summary}")
        except Exception as e:
            summaries.append(f"**Chunk {i+1}**: ❌ Error: {str(e)}")
    return f"**Chars**: {len(text)}\n**Time**: {time.time()-start:.2f}s\n\n" + "\n\n".join(summaries)

demo = gr.Interface(
    fn=summarize_file, inputs=gr.File(label="📄 PDF/TXT Notes", type="binary"), 
    outputs=gr.Textbox(label="📝 Summary"), 
    title="Fast Summarizer", description="300,000+ chars in ~20–30s (CPU)"
)

if __name__ == "__main__":
    try:
        demo.launch(share=False, server_port=7860)
    except Exception as e:
        print(f"❌ Gradio launch failed: {str(e)}")