feat: major platform expansion — Brain service, RSS reader, iOS app, AI assistants, Firefox extension
Brain Service: - Playwright stealth crawler replacing browserless (og:image, Readability, Reddit JSON API) - AI classification with tag definitions and folder assignment - YouTube video download via yt-dlp - Karakeep migration complete (96 items) - Taxonomy management (folders with icons/colors, tags) - Discovery shuffle, sort options, search (Meilisearch + pgvector) - Item tag/folder editing, card color accents RSS Reader Service: - Custom FastAPI reader replacing Miniflux - Feed management (add/delete/refresh), category support - Full article extraction via Readability - Background content fetching for new entries - Mark all read with confirmation - Infinite scroll, retention cleanup (30/60 day) - 17 feeds migrated from Miniflux iOS App (SwiftUI): - Native iOS 17+ app with @Observable architecture - Cookie-based auth, configurable gateway URL - Dashboard with custom background photo + frosted glass widgets - Full fitness module (today/templates/goals/food library) - AI assistant chat (fitness + brain, raw JSON state management) - 120fps ProMotion support AI Assistants (Gateway): - Unified dispatcher with fitness/brain domain detection - Fitness: natural language food logging, photo analysis, multi-item splitting - Brain: save/append/update/delete notes, search & answer, undo support - Madiha user gets fitness-only (brain disabled) Firefox Extension: - One-click save to Brain from any page - Login with platform credentials - Right-click context menu (save page/link/image) - Notes field for URL saves - Signed and published on AMO Other: - Reader bookmark button routes to Brain (was Karakeep) - Fitness food library with "Add" button + add-to-meal popup - Kindle send file size check (25MB SMTP2GO limit) - Atelier UI as default (useAtelierShell=true) - Mobile upload box in nav drawer Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Yusuf Suleman
@@ -12,6 +12,7 @@ from sqlalchemy.orm import selectinload
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from app.config import REDIS_URL, DATABASE_URL_SYNC
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from app.models.item import Item, ItemAsset
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from app.models.taxonomy import Folder, Tag, ItemTag # noqa: F401 — register FK targets
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log = logging.getLogger(__name__)
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@@ -34,7 +35,7 @@ async def _process_item(item_id: str):
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"""Full processing pipeline for a saved item."""
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from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine, async_sessionmaker
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from app.config import DATABASE_URL
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from app.services.ingest import fetch_url_content, take_screenshot, archive_html
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from app.services.ingest import crawl_url, save_screenshot_from_base64, download_og_image, archive_html
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from app.services.classify import classify_item
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from app.services.embed import generate_embedding
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from app.search.engine import index_item, ensure_meili_index
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@@ -62,42 +63,96 @@ async def _process_item(item_id: str):
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# ── Step 1: Fetch content for URLs ──
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if item.type == "link" and item.url:
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log.info(f"Fetching URL: {item.url}")
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content = await fetch_url_content(item.url)
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html_content = content.get("html")
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extracted_text = content.get("text") or extracted_text
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if not title:
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title = content.get("title")
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from app.services.ingest import (
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_is_youtube_url, download_youtube_thumbnail,
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download_youtube_video, fetch_youtube_metadata,
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)
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item.metadata_json = item.metadata_json or {}
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item.metadata_json["description"] = content.get("description")
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item.metadata_json["used_browserless"] = content.get("used_browserless", False)
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is_yt = _is_youtube_url(item.url)
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# Take screenshot
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screenshot_path = await take_screenshot(item.url, item.id)
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if screenshot_path:
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asset = ItemAsset(
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id=str(uuid.uuid4()),
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item_id=item.id,
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asset_type="screenshot",
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filename="screenshot.png",
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content_type="image/png",
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storage_path=screenshot_path,
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)
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db.add(asset)
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if is_yt:
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# YouTube: use oEmbed + thumbnail + yt-dlp (no crawler needed)
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log.info(f"Processing YouTube URL: {item.url}")
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yt_meta = await fetch_youtube_metadata(item.url)
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if yt_meta:
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if not title:
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title = yt_meta.get("title")
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extracted_text = f"YouTube: {yt_meta.get('title','')}\nBy: {yt_meta.get('author','')}"
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item.metadata_json["youtube"] = {
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"video_id": yt_meta.get("video_id"),
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"author": yt_meta.get("author"),
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"is_short": yt_meta.get("is_short", False),
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}
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item.metadata_json["description"] = f"YouTube video by {yt_meta.get('author','')}"
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# Archive HTML
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if html_content:
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html_path = await archive_html(html_content, item.id)
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if html_path:
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asset = ItemAsset(
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id=str(uuid.uuid4()),
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item_id=item.id,
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asset_type="archived_html",
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filename="page.html",
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content_type="text/html",
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storage_path=html_path,
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)
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db.add(asset)
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# Download video
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log.info(f"Downloading YouTube video: {item.url}")
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video_path, yt_info = await download_youtube_video(item.url, item.id)
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if video_path:
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db.add(ItemAsset(
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id=str(uuid.uuid4()), item_id=item.id,
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asset_type="video", filename=f"{yt_meta['video_id']}.mp4",
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content_type="video/mp4", storage_path=video_path,
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))
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if yt_info.get("duration"):
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item.metadata_json["youtube"]["duration"] = yt_info["duration"]
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if yt_info.get("description"):
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item.metadata_json["youtube"]["description"] = yt_info["description"][:500]
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extracted_text = f"YouTube: {title or ''}\nBy: {(yt_meta or {}).get('author','')}\n{yt_info['description'][:2000]}"
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# Thumbnail
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thumb_path = await download_youtube_thumbnail(item.url, item.id)
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if thumb_path:
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db.add(ItemAsset(
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id=str(uuid.uuid4()), item_id=item.id,
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asset_type="screenshot", filename="thumbnail.jpg",
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content_type="image/jpeg", storage_path=thumb_path,
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))
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else:
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# Regular URL: use Playwright crawler (stealth)
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log.info(f"Crawling URL: {item.url}")
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crawl = await crawl_url(item.url)
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html_content = crawl.get("html")
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extracted_text = crawl.get("text") or extracted_text
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if not title:
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title = crawl.get("title")
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item.metadata_json["description"] = crawl.get("description")
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item.metadata_json["author"] = crawl.get("author")
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item.metadata_json["status_code"] = crawl.get("status_code")
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# Screenshot (from crawler, base64 JPEG)
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if crawl.get("screenshot"):
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ss_path = await save_screenshot_from_base64(crawl["screenshot"], item.id)
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if ss_path:
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db.add(ItemAsset(
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id=str(uuid.uuid4()), item_id=item.id,
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asset_type="screenshot", filename="screenshot.jpg",
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content_type="image/jpeg", storage_path=ss_path,
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))
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# og:image (extracted from rendered DOM by crawler)
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og_url = crawl.get("og_image_url")
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if og_url:
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og_path = await download_og_image(og_url, item.id)
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if og_path:
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db.add(ItemAsset(
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id=str(uuid.uuid4()), item_id=item.id,
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asset_type="og_image", filename="og_image.jpg",
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content_type="image/jpeg", storage_path=og_path,
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))
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item.metadata_json["og_image_url"] = og_url
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# Archive HTML
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if html_content:
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html_path = await archive_html(html_content, item.id)
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if html_path:
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db.add(ItemAsset(
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id=str(uuid.uuid4()), item_id=item.id,
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asset_type="archived_html", filename="page.html",
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content_type="text/html", storage_path=html_path,
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))
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# ── Step 1b: Process uploaded files (PDF, image, document) ──
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if item.type in ("pdf", "image", "document", "file"):
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