{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 1: Create Assets from Raw PDFs\n",
    "\n",
    "This notebook processes raw PDFs and creates structured assets:\n",
    "- Page images (PNG at 300 DPI)\n",
    "- OCR text (AWS Textract)\n",
    "\n",
    "**Output**: Structured assets for benchmark creation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append(\"../src/assets\")\n",
    "\n",
    "from services.pdf_loader import PdfLoader\n",
    "from services.textract_ocr import TextractOcr\n",
    "from services.asset_writer import AssetWriter\n",
    "from services.asset_creator import AssetCreator"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "RAW_DATA_PATH = '../data/raw_pdfs'\n",
    "OUTPUT_PATH = '../data/assets'\n",
    "WORKERS = 10\n",
    "LIMIT = None  # Set to number to limit processing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load PDFs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "loader = PdfLoader(raw_data_path=RAW_DATA_PATH)\n",
    "documents = loader.get_all_documents()\n",
    "\n",
    "print(f\"Loaded {len(documents)} documents\")\n",
    "print(f\"Sample: {documents[0]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Assets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ocr = TextractOcr()\n",
    "writer = AssetWriter(output_base_path=OUTPUT_PATH)\n",
    "creator = AssetCreator(writer, ocr)\n",
    "\n",
    "results = creator.create_all(\n",
    "    documents=documents,\n",
    "    workers=WORKERS,\n",
    "    limit=LIMIT\n",
    ")\n",
    "\n",
    "print(f\"\\nResults: {results}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save Document Mapping (Optional)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "loader.save_document_mapping(\n",
    "    documents,\n",
    "    output_path='../data/document_mapping.csv'\n",
    ")\n",
    "\n",
    "print(\"Document mapping saved!\")"
   ]
  }
 ],
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