feat: uv config other feats

- add uv configuration for the backend
- update frontend to make auth work
- add new auth endpoints
- add bookmars feat
- add reader feat
This commit is contained in:
2026-06-03 22:06:01 -05:00
parent 730c748f5f
commit 6b4c0c43f8
137 changed files with 20319 additions and 2340 deletions
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from __future__ import annotations
import logging
from datetime import datetime, timezone
from django.core.files.base import ContentFile
from apps.books.models import EBook
from apps.books.services.openlibrary import (
HIGH_CONFIDENCE,
download_cover,
fetch_metadata,
)
logger = logging.getLogger(__name__)
def enrich_ebook_metadata(ebook: EBook) -> EBook:
"""Fetch Open Library metadata and update the ebook. Never raises to callers."""
user_title = ebook.title
user_author = ebook.author or ""
try:
result = fetch_metadata(user_title, user_author)
except Exception:
logger.exception("Open Library metadata fetch failed for ebook %s", ebook.pk)
return ebook
if result is None:
return ebook
now = datetime.now(timezone.utc).isoformat()
metadata = {
"source": "openlibrary",
"matched_at": now,
"match_language": result.match_language,
"match_score": result.match_score,
"match_status": result.match_status,
"user_input": {"title": user_title, "author": user_author},
"openlibrary": result.openlibrary,
}
ebook.metadata_json = metadata
update_fields = ["metadata_json", "updated_at"]
if result.match_status == "not_found":
ebook.save(update_fields=update_fields)
return ebook
ol = result.openlibrary
cover_id = ol.get("cover_id")
cover_missing = (
not ebook.cover_image
or not ebook.cover_image.name
or not ebook.cover_image.storage.exists(ebook.cover_image.name)
)
if cover_id and cover_missing:
if ebook.cover_image:
ebook.cover_image.delete(save=False)
cover_bytes = download_cover(int(cover_id))
if cover_bytes:
filename = f"ol_cover_{ebook.pk}_{cover_id}.jpg"
ebook.cover_image.save(filename, ContentFile(cover_bytes), save=False)
update_fields.append("cover_image")
if result.match_score >= HIGH_CONFIDENCE:
ol_title = ol.get("title")
ol_authors = ol.get("authors") or []
if ol_title:
ebook.title = ol_title[:512]
update_fields.append("title")
if ol_authors:
ebook.author = ol_authors[0][:256]
update_fields.append("author")
ebook.save(update_fields=list(dict.fromkeys(update_fields)))
return ebook
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from __future__ import annotations
import logging
import re
import unicodedata
from dataclasses import dataclass
from difflib import SequenceMatcher
from typing import Any
import httpx
from config.settings import settings
logger = logging.getLogger(__name__)
SEARCH_URL = "https://openlibrary.org/search.json"
COVERS_URL = "https://covers.openlibrary.org/b/id/{cover_id}-{size}.jpg"
SEARCH_FIELDS = (
"key,title,author_name,cover_i,first_publish_year,subject,language,"
"edition_key,number_of_pages_median,publisher"
)
HIGH_CONFIDENCE = 0.8
LOW_CONFIDENCE = 0.6
# EPUB release noise often copied from filenames, e.g. "Title [6494] (r2.3)"
_TITLE_NOISE_PATTERNS = (
re.compile(r"\s*\[\d+\]"), # [6494]
re.compile(r"\s*\([rv][\d.]+\)", re.IGNORECASE), # (r2.3), (v1.0)
re.compile(r"\s*\(rev[\d.]*\)", re.IGNORECASE), # (rev2)
)
def _sanitize_search_title(title: str) -> str:
cleaned = title.strip()
for pattern in _TITLE_NOISE_PATTERNS:
cleaned = pattern.sub("", cleaned)
return re.sub(r"\s+", " ", cleaned).strip()
@dataclass(frozen=True)
class OpenLibraryHit:
work_key: str
title: str
authors: list[str]
cover_id: int | None
first_publish_year: int | None
subjects: list[str]
languages: list[str]
publishers: list[str]
edition_key: str | None
number_of_pages_median: int | None
match_language: str
score: float
@dataclass(frozen=True)
class OpenLibraryMetadata:
match_language: str
match_score: float
match_status: str
openlibrary: dict[str, Any]
def _normalize(text: str) -> str:
cleaned = re.sub(r"[^\w\s]", " ", _strip_accents(text).lower())
return re.sub(r"\s+", " ", cleaned).strip()
def _strip_accents(text: str) -> str:
normalized = unicodedata.normalize("NFKD", text)
return "".join(ch for ch in normalized if not unicodedata.combining(ch))
def _build_search_params(
title: str,
author: str,
*,
lang: str | None,
search_mode: str,
) -> dict[str, str | int]:
title = title.strip()
author = author.strip()
params: dict[str, str | int] = {"limit": 10, "fields": SEARCH_FIELDS}
if search_mode == "spanish_q":
q_parts = ["language:spa", title]
if author:
q_parts.append(author)
params["q"] = " ".join(q_parts)
elif search_mode == "q":
params["q"] = " ".join(part for part in (title, author) if part)
elif search_mode == "q_unaccent":
params["q"] = " ".join(
part for part in (_strip_accents(title), _strip_accents(author) if author else "") if part
)
else:
params["title"] = title
if author:
params["author"] = author
if lang:
params["lang"] = lang
return params
def _title_similarity(a: str, b: str) -> float:
na, nb = _normalize(a), _normalize(b)
if not na or not nb:
return 0.0
if na in nb or nb in na:
return 1.0
return SequenceMatcher(None, na, nb).ratio()
def _author_overlap(user_author: str, ol_authors: list[str]) -> float:
if not user_author.strip():
return 0.5 if ol_authors else 0.0
user_tokens = set(_normalize(user_author).split())
if not user_tokens:
return 0.0
best = 0.0
for name in ol_authors:
name_tokens = set(_normalize(name).split())
if not name_tokens:
continue
overlap = len(user_tokens & name_tokens) / len(user_tokens)
best = max(best, overlap)
if user_tokens <= name_tokens or name_tokens <= user_tokens:
best = max(best, 0.95)
return best
def _score_hit(title: str, author: str, doc: dict[str, Any], *, lang: str) -> float:
ol_title = doc.get("title") or ""
ol_authors = doc.get("author_name") or []
title_score = _title_similarity(title, ol_title)
author_score = _author_overlap(author, ol_authors)
combined = (title_score * 0.6) + (author_score * 0.4)
if doc.get("cover_i"):
combined += 0.05
return min(combined, 1.0)
def _parse_hit(doc: dict[str, Any], *, lang: str, score: float) -> OpenLibraryHit:
edition_keys = doc.get("edition_key") or []
edition_key = edition_keys[0] if edition_keys else None
cover_id = doc.get("cover_i")
return OpenLibraryHit(
work_key=doc.get("key") or "",
title=doc.get("title") or "",
authors=list(doc.get("author_name") or []),
cover_id=int(cover_id) if cover_id else None,
first_publish_year=doc.get("first_publish_year"),
subjects=list(doc.get("subject") or [])[:10],
languages=list(doc.get("language") or []),
publishers=list(doc.get("publisher") or [])[:5],
edition_key=edition_key,
number_of_pages_median=doc.get("number_of_pages_median"),
match_language=lang,
score=score,
)
def build_cover_url(cover_id: int, size: str = "L") -> str:
return COVERS_URL.format(cover_id=cover_id, size=size)
def _client() -> httpx.Client:
read_timeout = settings.OPENLIBRARY_TIMEOUT_SECONDS
connect_timeout = settings.OPENLIBRARY_CONNECT_TIMEOUT_SECONDS
return httpx.Client(
timeout=httpx.Timeout(
connect=connect_timeout,
read=read_timeout,
write=read_timeout,
pool=connect_timeout,
),
headers={"User-Agent": settings.OPENLIBRARY_USER_AGENT},
follow_redirects=True,
)
def search_works(
title: str,
author: str,
*,
lang: str | None = None,
search_mode: str = "title",
client: httpx.Client | None = None,
) -> list[OpenLibraryHit]:
if not title.strip():
return []
params = _build_search_params(title, author, lang=lang, search_mode=search_mode)
try:
if client is not None:
response = client.get(SEARCH_URL, params=params)
response.raise_for_status()
docs = response.json().get("docs") or []
else:
with _client() as owned_client:
response = owned_client.get(SEARCH_URL, params=params)
response.raise_for_status()
docs = response.json().get("docs") or []
except (httpx.HTTPError, ValueError) as exc:
logger.warning("Open Library search failed: %s", exc)
return []
hits: list[OpenLibraryHit] = []
for doc in docs:
score = _score_hit(title, author, doc, lang=lang or "")
if score < LOW_CONFIDENCE:
continue
hits.append(_parse_hit(doc, lang=lang or "", score=score))
hits.sort(key=lambda h: (h.score, h.cover_id is not None), reverse=True)
return hits
def pick_best_match(title: str, author: str, hits: list[OpenLibraryHit]) -> OpenLibraryHit | None:
return hits[0] if hits else None
def download_cover(cover_id: int) -> bytes | None:
url = build_cover_url(cover_id, size="L")
try:
with _client() as client:
response = client.get(url)
if response.status_code == 404:
return None
response.raise_for_status()
content_type = response.headers.get("content-type", "")
if not content_type.startswith("image/"):
return None
return response.content
except httpx.HTTPError as exc:
logger.warning("Open Library cover download failed for %s: %s", cover_id, exc)
return None
def _hit_to_openlibrary_dict(hit: OpenLibraryHit) -> dict[str, Any]:
return {
"work_key": hit.work_key,
"edition_key": hit.edition_key,
"title": hit.title,
"authors": hit.authors,
"cover_id": hit.cover_id,
"cover_url": build_cover_url(hit.cover_id) if hit.cover_id else None,
"first_publish_year": hit.first_publish_year,
"subjects": hit.subjects,
"languages": hit.languages,
"publishers": hit.publishers,
"number_of_pages_median": hit.number_of_pages_median,
}
def fetch_metadata(title: str, author: str) -> OpenLibraryMetadata | None:
if not settings.OPENLIBRARY_ENABLED:
return None
preferred = settings.OPENLIBRARY_PREFERRED_LANG
fallback = settings.OPENLIBRARY_FALLBACK_LANG
search_title = _sanitize_search_title(title)
if not search_title:
return OpenLibraryMetadata(
match_language=preferred,
match_score=0.0,
match_status="not_found",
openlibrary={},
)
search_plan: list[tuple[str, str | None]] = [
("spanish_q", preferred),
("title", preferred),
("q", None),
("q_unaccent", None),
]
if fallback != preferred:
search_plan.extend([("title", fallback), ("q", fallback)])
hits: list[OpenLibraryHit] = []
with _client() as client:
for search_mode, lang in search_plan:
hits = search_works(search_title, author, lang=lang, search_mode=search_mode, client=client)
if hits:
break
hit = pick_best_match(title, author, hits)
if not hit:
return OpenLibraryMetadata(
match_language=preferred,
match_score=0.0,
match_status="not_found",
openlibrary={},
)
status = "matched" if hit.score >= HIGH_CONFIDENCE else "partial"
return OpenLibraryMetadata(
match_language=hit.match_language,
match_score=hit.score,
match_status=status,
openlibrary=_hit_to_openlibrary_dict(hit),
)
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"""Extract TOC, metadata, and page count from uploaded EPUB/PDF files."""
from __future__ import annotations
import logging
import os
from pathlib import Path
from typing import Any
from apps.books.models import BookChapter, EBook
logger = logging.getLogger(__name__)
def process_ebook(file_path: str, original_filename: str | None = None) -> dict[str, Any]:
"""Parse an e-book file and return format, metadata, TOC, and page count."""
ext = Path(original_filename or file_path).suffix.lower()
if ext == ".epub" or file_path.lower().endswith(".epub"):
return _process_epub(file_path)
if ext == ".pdf" or file_path.lower().endswith(".pdf"):
return _process_pdf(file_path)
return {"format": ext.lstrip(".") or "unknown", "page_count": 0, "metadata": {}, "toc": []}
def store_chapters(ebook: EBook, toc: list[dict[str, Any]], parent_index: int = 0) -> None:
"""Recursively store TOC entries as BookChapter records."""
for idx, entry in enumerate(toc):
BookChapter.objects.create(
ebook=ebook,
title=entry.get("title", "Untitled"),
index=parent_index + idx,
href=entry.get("href", ""),
children=entry.get("children", []),
)
children = entry.get("children", [])
if children:
store_chapters(ebook, children, parent_index + idx + 1)
def apply_processing_to_ebook(ebook: EBook) -> dict[str, Any]:
"""Run processing on an EBook instance and persist chapters + metadata."""
if not ebook.file:
raise ValueError("No file found for this e-book.")
file_path = ebook.file.path
result = process_ebook(file_path, original_filename=ebook.filename())
ebook.format = result.get("format", ebook.format)
ebook.page_count = result.get("page_count", 0)
file_metadata = result.get("metadata") or {}
if file_metadata:
merged = dict(ebook.metadata_json or {})
merged["file"] = file_metadata
ebook.metadata_json = merged
ebook.save(update_fields=["format", "page_count", "metadata_json", "updated_at"])
raw_toc: list[dict[str, Any]] = result.get("toc", [])
BookChapter.objects.filter(ebook=ebook).delete()
store_chapters(ebook, raw_toc)
return {
"format": ebook.format,
"page_count": ebook.page_count,
"metadata": ebook.metadata_json,
"toc_count": len(raw_toc),
"status": "processed",
}
def _process_epub(file_path: str) -> dict[str, Any]:
from ebooklib import epub, ITEM_DOCUMENT
book = epub.read_epub(file_path)
metadata = _extract_epub_metadata(book)
toc = _extract_epub_toc(book)
if not toc:
toc = _fallback_toc_from_spine(book, ITEM_DOCUMENT)
flat_count = _count_toc_entries(toc)
page_count = flat_count or len(book.spine)
return {
"format": "epub",
"page_count": page_count,
"metadata": metadata,
"toc": toc,
}
def _process_pdf(file_path: str) -> dict[str, Any]:
return {"format": "pdf", "page_count": 0, "metadata": {}, "toc": []}
def _extract_epub_metadata(book) -> dict[str, Any]:
metadata: dict[str, Any] = {}
def first(namespace: str, name: str) -> str:
values = book.get_metadata(namespace, name)
if values:
return str(values[0][0])
return ""
title = first("DC", "title")
if title:
metadata["title"] = title
creator = first("DC", "creator")
if creator:
metadata["author"] = creator
language = first("DC", "language")
if language:
metadata["language"] = language
identifier = first("DC", "identifier")
if identifier:
metadata["identifier"] = identifier
return metadata
def _parse_toc_item(item) -> dict[str, Any]:
from ebooklib import epub
if isinstance(item, epub.Link):
return {
"title": item.title or "Untitled",
"href": item.href or "",
"children": [],
}
if isinstance(item, tuple):
section, children = item
entry = {
"title": getattr(section, "title", None) or "Untitled",
"href": getattr(section, "href", None) or "",
"children": [],
}
for child in children:
entry["children"].append(_parse_toc_item(child))
return entry
if hasattr(item, "title"):
return {
"title": item.title or "Untitled",
"href": getattr(item, "href", "") or "",
"children": [],
}
return {"title": "Untitled", "href": "", "children": []}
def _extract_epub_toc(book) -> list[dict[str, Any]]:
return [_parse_toc_item(item) for item in book.toc]
def _fallback_toc_from_spine(book, item_document_type) -> list[dict[str, Any]]:
toc: list[dict[str, Any]] = []
seen: set[str] = set()
chapter_num = 0
for spine_entry in book.spine:
item_id = spine_entry[0] if isinstance(spine_entry, tuple) else spine_entry
item = book.get_item_with_id(item_id)
if not item or item.get_type() != item_document_type:
continue
href = item.get_name() or ""
if not href or href in seen:
continue
seen.add(href)
chapter_num += 1
title = os.path.splitext(os.path.basename(href))[0] or f"Chapter {chapter_num}"
toc.append({"title": title.replace("_", " ").replace("-", " "), "href": href, "children": []})
return toc
def _count_toc_entries(toc: list[dict[str, Any]]) -> int:
count = 0
for entry in toc:
count += 1
count += _count_toc_entries(entry.get("children", []))
return count