app.py

import spaces
import gradio as gr
import fitz  # PyMuPDF
import tempfile
import os
from PIL import Image
import pytesseract

def clean_ocr_text(text):
    lines = text.splitlines()
    cleaned_lines = []

    for line in lines:
        line = line.strip()
        if line and not line.isspace():
            cleaned_lines.append(line)

    return "\n".join(cleaned_lines)

def extract_text_markdown(doc):
    markdown_output = ""
    image_counter = 1

    for page in doc:
        blocks = page.get_text("dict")["blocks"]
        elements = []

        for b in blocks:
            y = b["bbox"][1]
            if b["type"] == 0:  # Texto
                for line in b["lines"]:
                    line_y = line["bbox"][1]
                    line_text = " ".join([span["text"] for span in line["spans"]]).strip()
                    max_font_size = max([span.get("size", 10) for span in line["spans"]])
                    if line_text:
                        elements.append((line_y, line_text, max_font_size))
            elif b["type"] == 1:  # Imagen
                elements.append((y, f"![imagen_{image_counter}](#)", 10))
                image_counter += 1

        elements.sort(key=lambda x: x[0])

        previous_y = None
        previous_font = None

        for y, text, font_size in elements:
            is_header = font_size >= 14

            if previous_y is not None and abs(y - previous_y) > 10:
                markdown_output += "\n"

            if is_header:
                markdown_output += f"\n### {text.strip()}\n"
            else:
                markdown_output += text.strip() + "\n"

            previous_y = y
            previous_font = font_size

        markdown_output += "\n---\n\n"

    return markdown_output.strip()

@spaces.GPU
def convert(pdf_file):
    doc = fitz.open(pdf_file)
    markdown_output = ""
    image_counter = 1

    for page_num in range(len(doc)):
        page = doc[page_num]
        text = page.get_text("text").strip()

        if len(text) > 30:
            # Página con texto normal
            markdown_output += extract_text_markdown([page]) + "\n"
        else:
            # Página sin texto: usar OCR
            pix = page.get_pixmap(dpi=300)
            img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
            ocr_text = pytesseract.image_to_string(img, lang="spa")
            markdown_output += clean_ocr_text(ocr_text) + "\n"

        markdown_output += "\n---\n\n"

    return markdown_output.strip(), {}

gr.Interface(
    fn=convert,
    inputs=[gr.File(label="Sube tu PDF", type="filepath")],
    outputs=[gr.Text(label="Markdown estructurado"), gr.JSON(label="Metadata")],
).launch()