Add materials, exam images, storage quota, and API guide

Upload documents for AI context, exam images for Moodle questions, per-template storage limits, embedded images in XML export, and GUIA_API_Y_FLUJO.md with full endpoint documentation.

backend/app/services/document_extractor.py

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+from pathlib import Path
+
+from app.core.errors import AppError
+
+SUPPORTED_EXTENSIONS = {
+    ".pdf": "application/pdf",
+    ".docx": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
+    ".txt": "text/plain",
+    ".md": "text/markdown",
+    ".png": "image/png",
+    ".jpg": "image/jpeg",
+    ".jpeg": "image/jpeg",
+    ".webp": "image/webp",
+}
+
+
+class DocumentExtractor:
+    def extract(self, file_path: Path, mime_type: str) -> str:
+        suffix = file_path.suffix.lower()
+        if mime_type == "application/pdf" or suffix == ".pdf":
+            return self._extract_pdf(file_path)
+        if (
+            mime_type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
+            or suffix == ".docx"
+        ):
+            return self._extract_docx(file_path)
+        if mime_type.startswith("text/") or suffix in {".txt", ".md"}:
+            return self._extract_text(file_path)
+        if mime_type.startswith("image/") or suffix in {".png", ".jpg", ".jpeg", ".webp"}:
+            return self._extract_image(file_path)
+        raise AppError(f"Unsupported file type: {mime_type}", status_code=415, code="unsupported_media")
+
+    def _extract_pdf(self, file_path: Path) -> str:
+        from pypdf import PdfReader
+
+        reader = PdfReader(str(file_path))
+        parts = [page.extract_text() or "" for page in reader.pages]
+        text = "\n".join(parts).strip()
+        if not text:
+            raise AppError("PDF does not contain extractable text", status_code=422, code="empty_extraction")
+        return text
+
+    def _extract_docx(self, file_path: Path) -> str:
+        from docx import Document
+
+        document = Document(str(file_path))
+        parts = [paragraph.text.strip() for paragraph in document.paragraphs if paragraph.text.strip()]
+        text = "\n".join(parts).strip()
+        if not text:
+            raise AppError("DOCX does not contain extractable text", status_code=422, code="empty_extraction")
+        return text
+
+    def _extract_text(self, file_path: Path) -> str:
+        text = file_path.read_text(encoding="utf-8", errors="ignore").strip()
+        if not text:
+            raise AppError("Text file is empty", status_code=422, code="empty_extraction")
+        return text
+
+    def _extract_image(self, file_path: Path) -> str:
+        try:
+            import pytesseract
+            from PIL import Image
+        except ImportError as exc:
+            raise AppError(
+                "Image OCR is not available on this server",
+                status_code=503,
+                code="ocr_unavailable",
+            ) from exc
+
+        image = Image.open(file_path)
+        text = pytesseract.image_to_string(image, lang="spa+eng").strip()
+        if not text:
+            raise AppError("Image does not contain recognizable text", status_code=422, code="empty_extraction")
+        return text