feat: v0.6.0 — collapse policy, session limiter, Claude Code provider, prune, browser auth, media downloads
This commit is contained in:
JesseMarkowitz
@@ -8,58 +8,198 @@ of these additions straightforward.
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- v0.1.0 — Core export: ChatGPT + Claude, incremental sync, Markdown + JSON output
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- v0.2.0 — Joplin import automation (`joplin` command, create/update notes, notebook auto-creation)
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- v0.4.0 — Rich content support: typed message blocks (text, code, thinking, tool_use, tool_result, image_placeholder, file_placeholder, unknown); ChatGPT voice transcripts as text + audio placeholders; Custom Instructions extraction; data-loss visibility via `LossReport` summary and visible `unknown` blocks
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- v0.5.0 — Nested Joplin notebooks, date-prefixed note titles, flat year folders
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- v0.6.0 — Collapse tool retrieval dumps & hidden context (`EXPORTER_HIDDEN_CONTENT` policy; roadmap item 1); session limiter + request pacing (`MAX_CONVERSATIONS_PER_RUN`, `REQUEST_DELAY`; roadmap item 6)
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---
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## Export `--force` Flag (v0.2.x)
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# Roadmap (decided 2026-06-12)
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Add `--force` to the `export` command to re-export already-cached conversations
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without permanently clearing the entire manifest. Useful for re-generating files
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after changing the Markdown template or output structure.
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Priorities reflect the tool's primary purpose — a trustworthy backup so that
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conversation data is not lost if a provider account is ever closed — plus the
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day-to-day friction of weekly ChatGPT token refresh, and the long-term goal
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of running headless as a StartOS service.
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Implementation: pass a `force=True` flag to `cache.get_new_or_updated()`, which
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returns all conversations regardless of cache state when force is True.
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**Now (in order):**
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1. ~~Collapse tool retrieval dumps & hidden context~~ — **shipped in v0.6.0**
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(full-archive re-export still pending; see entry below)
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2. ~~Brave cookie auto-extraction~~ — **shipped in v0.6.0** (note: runs on
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whichever machine hosts the browser — Brave is not on this Linux box)
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3. ~~Claude Code session provider~~ — **shipped in v0.6.0**
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4. ~~Archive hygiene — `prune` + `doctor` integrity check~~ — **shipped in v0.6.0**
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Current workaround: `python -m src.main cache --clear` then re-run export.
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**Soon, but later:**
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## Joplin `--force` Flag (v0.2.x)
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5. ~~Binary content downloads~~ — **shipped in v0.6.0**
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6. ~~Per-session download limiter + polite pacing~~ — **shipped in v0.6.0**
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7. Scheduled / watch mode → StartOS service packaging (long-term destination)
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Similarly, add `--force` to the `joplin` command to re-sync all cached
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conversations to Joplin regardless of whether they've been synced before.
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Useful after making formatting changes to the Markdown exporter.
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Implementation: in `get_joplin_pending()`, return all entries that have a
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`file_path` when `force=True`, ignoring `joplin_synced_at`.
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## Per-Conversation Cache Reset (v0.2.x)
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Add `cache --reset --conversation <id>` to force re-export or re-sync of a
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single conversation without clearing the entire provider cache.
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Current workaround: manually edit `~/.ai-chat-exporter/manifest.json` and
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delete the entry, then re-run export.
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**Deprioritized** (entries kept at the bottom of this file; revisit on
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demand): `--force` flags, per-conversation cache reset, official export-ZIP
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fallback, o1/o3 reasoning reclassification, Obsidian output, token expiry
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notifications (largely superseded by cookie auto-extraction), search command.
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Additional web providers (Gemini/Grok/Perplexity) are explicitly out of
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scope — no significant usage to archive.
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---
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## Official API Fallback (v0.3.0)
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## 1. Collapse Tool Retrieval Dumps & Hidden Context — SHIPPED v0.6.0
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If the unofficial internal web API approach breaks, migrate to official export
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file parsing as a fallback:
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- ChatGPT: parse `conversations.json` from Settings → Export Data
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- Claude: parse `conversations.json` from Settings → Privacy → Export Data
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**Implemented 2026-06-12** as designed below, with one scoping correction
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from live recon: the retrieval dumps are NOT flagged
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`is_visually_hidden_from_conversation` — `author.name == "file_search"` is
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the discriminator (the hidden flag only marks Custom Instructions and small
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system stubs). Verified live: worst files shrink 93% (524KB → 36KB).
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Remaining step: full-archive re-export (`cache --clear` + `export`) +
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Joplin re-sync, at the user's chosen time.
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The `BaseProvider` abstract class is intentionally designed so that a
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`FileProvider` subclass can implement the same interface
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(`list_conversations`, `get_conversation`, `normalize_conversation`)
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without any changes to cache, exporters, or CLI code.
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**Problem (measured 2026-06-12 against a full fresh export):** 45% of the
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entire 11.2MB archive (260 files) is tool-role messages; 29 files are
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majority tool-dump. Worst case: a 524KB conversation where 495KB (94%, 64
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messages) is ChatGPT's file-retrieval tool re-injecting the full text of
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the user's own attached documents, the same files dumped dozens of times
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per conversation. These messages were invisible in the ChatGPT web UI;
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they appear in exports because v0.4.0 lifted the role filter to fix silent
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data loss. Custom Instructions hidden-context blocks are a minor secondary
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case (~2KB, once per conversation) — the originally planned
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`EXPORTER_INCLUDE_HIDDEN_CONTEXT` toggle alone would not help: the worst
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file contains zero hidden-context blocks.
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To add this: implement `src/providers/file_chatgpt.py` and
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`src/providers/file_claude.py`, then add `--input-file` flag to the
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export command to accept a pre-downloaded export ZIP or JSON.
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**Fix: collapse, don't drop** (consistent with the no-silent-drop rule):
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---
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- `EXPORTER_HIDDEN_CONTENT=full|placeholder|omit` env var, default
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`placeholder`, plus a `--hidden-content` CLI override on `export`.
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- `placeholder` renders affected messages as one line with type and size:
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`> 🔧 Tool output (file_search, 24KB) — omitted
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(EXPORTER_HIDDEN_CONTENT=full to keep)`. Expected effect: archive
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roughly halves; worst files shrink ~90%.
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- **Scope — collapse:** (a) tool-role retrieval dumps, identified by raw
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`author.name` (`file_search`, `myfiles_browser`, …) in the API response
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(the rendered Markdown only shows a generic "🔧 Tool" label, so the
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decision must happen in the provider, not the renderer); (b) messages
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flagged `is_visually_hidden_from_conversation`, including
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`user_editable_context` / `model_editable_context` (Custom
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Instructions) — subsumes the old suppress-hidden-context idea.
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- **Scope — keep at full size:** code-execution `tool_result` blocks and
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web-search results; those are usually content the user wants.
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- Count collapsed messages in the post-export summary so the omission
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stays visible (mirror the LossReport presentation, but as intentional
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policy, not loss).
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## Binary Content Downloads (v0.5.0)
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Re-export workflow after shipping: `cache --clear` + `export` (same as
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the v0.4.0 migration).
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## 2. Brave Cookie Auto-Extraction — SHIPPED v0.6.0
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**Implemented 2026-06-12**: `auth --from-browser [browser]`
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(`src/browser_tokens.py`, browser-cookie3 dependency, defaults to brave;
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chrome/chromium/edge/firefox also supported). Extracted tokens are validated
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against the live API before `.env` is touched. **Discovered during
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implementation: Brave is not installed on this machine** — the logged-in
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browser lives elsewhere, so the flag only helps when the exporter runs on
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that machine (verified the graceful-failure path here; the happy path is
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covered by mocked tests). This strengthens the case for the StartOS
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token-push mechanism (entry 8).
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Pull session tokens directly from the Brave browser profile instead of the
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weekly manual DevTools dance. `auth` gains an "extract from browser" path
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(with the manual flow kept as fallback); a later iteration could let
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`doctor` or a 401 handler suggest/perform a re-extract automatically.
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- Brave on Linux follows the Chromium pattern: cookies SQLite at
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`~/.config/BraveSoftware/Brave-Browser/Default/Cookies`, values
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AES-128-CBC encrypted with a key derived from the OS keyring secret
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("Brave Safe Storage" via SecretService/kwallet, or the `peanuts` v10
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fallback). Well-trodden territory — evaluate a small dependency
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(`browser_cookie3`-style) vs. a focused in-repo implementation.
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- Extract `__Secure-next-auth.session-token.0` / `.1` from `chatgpt.com`
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and `sessionKey` from `claude.ai`; write to `.env` through the existing
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auth-wizard write path (tokens never echoed).
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- Brave must be the user's logged-in browser (it is); detect a locked /
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unreadable cookie DB (Brave running with the DB exclusively locked) and
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fall back to the manual flow with a clear message.
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- Does **not** solve headless/StartOS — no browser on the server. That
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needs a token-push mechanism, tracked under the StartOS entry.
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## 3. Claude Code Session Provider — SHIPPED v0.6.0
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**Implemented 2026-06-12** as designed below (`src/providers/claude_code.py`,
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`--provider claude-code`, `CLAUDE_CODE_DIR` override). Additional findings
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during implementation: `isSidechain` records are subagent transcripts (skipped),
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`isMeta` marks harness-generated user records (skipped), and listing/normalized
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`updated_at` must both use file mtime or the cache would re-export every
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session every run. First export: 25 sessions, 19MB JSONL → 804KB Markdown.
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Archive local Claude Code session transcripts. No tokens, no rate limits,
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no ToS risk — the data is already on disk but lives in a single JSONL per
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session that Claude Code may clean up, and it contains deliverables
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(reviews, plans, analyses) that exist nowhere else.
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Decisions (2026-06-12):
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- **Rendering: prose-only.** Keep user prompts and assistant text
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(including full deliverable write-ups); collapse tool activity to
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one-line placeholders (`> 🔧 Tool activity — 14 calls (Read ×9, Bash ×2),
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86KB — omitted`); **exclude thinking blocks**.
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- **Joplin: sync enabled.** Each coding project becomes a notebook nested
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under an **"AI-Claude"** parent notebook (nested-notebook support shipped
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in v0.5.0).
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Data facts (measured 2026-06-12):
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- Source: `~/.claude/projects/<munged-cwd>/<session-uuid>.jsonl`.
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Currently 29 sessions, 18.8MB total, largest 3.8MB.
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- Representative 2.1MB session: tool_result 436KB, tool_use 122KB,
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thinking 104KB, dialogue prose only ~24KB (~4%) — collapsing tool
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activity is what makes these exports readable.
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- Record types: `user` / `assistant` (Anthropic-style `message.content`
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block arrays) plus harness records: `ai-title` (use for note title and
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filename slug), `last-prompt`, `file-history-snapshot`, `attachment`,
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`permission-mode`, `system` (skip). Strip harness noise from user
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messages (`<local-command-caveat>`, `<command-name>` blocks).
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Implementation shape: new `src/providers/claude_code.py` implementing the
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`BaseProvider` interface — `list_conversations` scans project dirs,
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`get_conversation` parses the JSONL, `normalize_conversation` maps onto the
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existing block schema (content is already block-shaped: text / tool_use /
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tool_result / thinking). Incremental sync via file mtime/size recorded in
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the existing manifest. Project name derives from the munged cwd dirname.
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## 4. Archive Hygiene: `prune` Command + Manifest Integrity — SHIPPED v0.6.0
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**Implemented 2026-06-12** as designed below, plus an empty-manifest guard
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(refuses to prune right after `cache --clear`). First live run removed 420
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stale files (9.4 MB, old-layout trees + `_.md` orphans); doctor now reports
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manifest↔disk integrity (293/293 after the run).
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A backup is only trustworthy if the on-disk tree matches the manifest.
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Observed 2026-06-12: pre-v0.5.0 layout trees (`tspc-expertcouncil/2025/`)
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and `_.md` no-ID orphans (from the empty-conversation-id bug fixed in
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v0.4.1) sit alongside current exports and would double-sync into Joplin.
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- `prune` command: delete export files not referenced by the manifest.
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`--dry-run` (default off, but always print the list before deleting)
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shows what would be removed and why (old layout / orphan / unknown).
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- `doctor` extension: verify every manifest entry's `file_path` exists on
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disk; report missing files (re-export candidates) and unreferenced files
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(prune candidates).
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## 5. Binary Content Downloads — SHIPPED v0.6.0
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**Implemented 2026-06-12** (`src/media.py`, `EXPORTER_DOWNLOAD_MEDIA`,
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`download_asset`/`parse_asset_file_id` on the ChatGPT provider, Joplin
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`create_resource` + `upload_media_and_rewrite`). Live recon settled the
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download mechanism: `GET /backend-api/files/{id}/download` returns a signed
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`download_url`; a second GET yields the bytes (works for user uploads;
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older AI-generated images 404 — expired server-side, handled gracefully).
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Asset refs come in three shapes — `sediment://file_…`,
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`sediment://<hash>#file_…#p_N.png` (generated), `file-service://…`. Archive
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scan: 14 images (4 uploads / 10 generated) + 556 audio clips ≈162MB, so
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images-only is the default and audio is opt-in via `all`.
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Original notes below.
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**Priority note (2026-06-12): "later, but soon" — under the
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backup-if-account-closes goal, embedded images are part of the data that
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would be lost; placeholders alone don't preserve them.**
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v0.4.0 ships placeholders for images and audio assets but does not download
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the binary content. The `_safe_fence`-wrapped placeholders include the asset
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@@ -82,24 +222,46 @@ The block-level schema is already in place — only the file-fetch + rewrite
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layer needs to be added. See the `image_placeholder` and `file_placeholder`
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block definitions in `src/blocks.py`.
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## Reclassify o1/o3 Reasoning Subparts (v0.4.1)
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## 6. Per-Session Download Limiter — SHIPPED v0.6.0
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v0.4.0 leaves dict parts inside `text` content_type messages with shape
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`{"summary": ..., "content": ...}` rendered as plain text (defensive — the
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shape was inferred from a code comment, not captured live). Once a real
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reasoning conversation is captured, reclassify these as `thinking` blocks.
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**Implemented 2026-06-12** as designed below: `--max-conversations N` /
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`MAX_CONVERSATIONS_PER_RUN` session cap with deferred-count reporting, and
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`REQUEST_DELAY` pacing (default 1.0s ±25% jitter) in `BaseProvider._request`.
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Verified live: a 2-pending run with cap 1 exported one, deferred one, and
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the re-run picked it up.
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## Suppress Hidden Context (v0.4.x)
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Cap how many conversations are downloaded in a single `export` run so the
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tool never hammers the ChatGPT/Claude internal APIs with a large burst —
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most importantly on the very first export, which otherwise fetches the
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entire conversation history in one session. Because every run is resumable
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(the manifest records each conversation immediately), a capped run simply
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exports the first N pending conversations and the next run picks up where
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it left off. This keeps traffic looking like a human-paced session rather
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than a scraper, reducing the risk of rate limiting or account flags.
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If Custom Instructions duplication across conversations becomes a storage
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problem, add `EXPORTER_INCLUDE_HIDDEN_CONTEXT=false` env var. The toggle is
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a single `os.getenv()` check at the start of
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`_extract_editable_context_blocks` in `src/providers/chatgpt.py` — return
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empty list if disabled.
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Two complementary pieces:
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---
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1. **Session cap** — `--max-conversations N` flag (and
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`MAX_CONVERSATIONS_PER_RUN` env default). Implementation: in the
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`export` command, slice the pending list after the cache filter:
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`to_export = to_export[:n]`. On exit, print exported-vs-remaining
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counts (reuse the message format from the 429 early-exit path) and
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remind the user to re-run to continue.
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2. **Polite pacing** — `REQUEST_DELAY` env var (seconds, with small
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random jitter) slept between per-conversation detail fetches in
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`BaseProvider`, so even a capped run doesn't fire requests
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back-to-back. The existing 429 backoff in `_request` stays as the
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reactive safety net.
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## Scheduled / Watch Mode (v0.5.0)
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Note: the conversation *listing* (paginated, 100/page) still runs in full
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each time so the cache comparison works — the cap applies to the heavy
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per-conversation detail fetches, which dominate request volume.
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Together with watch mode, this is a stepping stone to the StartOS service:
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a scheduled, capped, politely-paced export is the traffic profile a
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headless deployment needs.
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## 7. Scheduled / Watch Mode
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Add a `watch` command (or cron integration helper) to run exports automatically
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on a schedule:
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@@ -116,9 +278,84 @@ Implementation: simple loop with `time.sleep()`, or emit a crontab entry
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string that calls the export and joplin commands in sequence. A `--once`
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flag would do a single run then exit (useful for cron itself).
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Stepping stone to the StartOS service (below).
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## 8. StartOS Service Packaging (long-term destination)
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Run the exporter headless as a StartOS service: scheduled export + sync to
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a Joplin Server instance, so the backup happens without a desktop in the
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loop.
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- Building blocks needed first: watch mode (#7), session limiter (#6),
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and a Joplin Server (vs. desktop Web Clipper) sync target.
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- **Hard problem, flagged early:** session-token freshness without a
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browser. ChatGPT tokens last ~7 days; there is no browser on the server
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to re-extract from. Candidate mechanisms: a service config action the
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user pastes fresh tokens into periodically, or a future browser
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extension that pushes tokens to the server. Cookie auto-extraction (#2)
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only solves the desktop case.
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---
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## Obsidian Vault Output (v0.5.0)
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# Deprioritized
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Kept for reference; not on the active roadmap.
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## Export `--force` Flag
|
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|
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Add `--force` to the `export` command to re-export already-cached conversations
|
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without permanently clearing the entire manifest. Useful for re-generating files
|
||||
after changing the Markdown template or output structure.
|
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|
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Implementation: pass a `force=True` flag to `cache.get_new_or_updated()`, which
|
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returns all conversations regardless of cache state when force is True.
|
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|
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Current workaround: `python -m src.main cache --clear` then re-run export.
|
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|
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## Joplin `--force` Flag
|
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|
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Similarly, add `--force` to the `joplin` command to re-sync all cached
|
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conversations to Joplin regardless of whether they've been synced before.
|
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Useful after making formatting changes to the Markdown exporter.
|
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|
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Implementation: in `get_joplin_pending()`, return all entries that have a
|
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`file_path` when `force=True`, ignoring `joplin_synced_at`.
|
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|
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## Per-Conversation Cache Reset
|
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|
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Add `cache --reset --conversation <id>` to force re-export or re-sync of a
|
||||
single conversation without clearing the entire provider cache.
|
||||
|
||||
Current workaround: manually edit `~/.ai-chat-exporter/manifest.json` and
|
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delete the entry, then re-run export.
|
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|
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## Official API Fallback
|
||||
|
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If the unofficial internal web API approach breaks, migrate to official export
|
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file parsing as a fallback:
|
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- ChatGPT: parse `conversations.json` from Settings → Export Data
|
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- Claude: parse `conversations.json` from Settings → Privacy → Export Data
|
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|
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The `BaseProvider` abstract class is intentionally designed so that a
|
||||
`FileProvider` subclass can implement the same interface
|
||||
(`list_conversations`, `get_conversation`, `normalize_conversation`)
|
||||
without any changes to cache, exporters, or CLI code.
|
||||
|
||||
To add this: implement `src/providers/file_chatgpt.py` and
|
||||
`src/providers/file_claude.py`, then add `--input-file` flag to the
|
||||
export command to accept a pre-downloaded export ZIP or JSON.
|
||||
|
||||
Deprioritized 2026-06-12: the official ChatGPT export does not cover what
|
||||
this user needs (project data), so it isn't a real fallback here.
|
||||
|
||||
## Reclassify o1/o3 Reasoning Subparts
|
||||
|
||||
v0.4.0 leaves dict parts inside `text` content_type messages with shape
|
||||
`{"summary": ..., "content": ...}` rendered as plain text (defensive — the
|
||||
shape was inferred from a code comment, not captured live). Once a real
|
||||
reasoning conversation is captured, reclassify these as `thinking` blocks.
|
||||
|
||||
## Obsidian Vault Output
|
||||
|
||||
Add an `obsidian` command (or `--target obsidian` flag) to sync exported
|
||||
conversations into an Obsidian vault directory. The current Markdown format
|
||||
@@ -134,28 +371,7 @@ Obsidian. An `ObsidianSyncer` class (mirroring `JoplinClient`) would simply
|
||||
copy files to the vault directory and maintain a flat or nested folder
|
||||
structure matching the user's Obsidian setup. No API needed — just file I/O.
|
||||
|
||||
---
|
||||
|
||||
## Joplin Nested Notebooks (future)
|
||||
|
||||
Currently notebooks are flat: `ChatGPT - My Project`. Joplin supports nested
|
||||
notebooks via `parent_id`. A future option (`JOPLIN_NESTED_NOTEBOOKS=true`)
|
||||
could create a two-level hierarchy:
|
||||
|
||||
```
|
||||
ChatGPT/
|
||||
My Project/
|
||||
No Project/
|
||||
Claude/
|
||||
Budget Tracker/
|
||||
```
|
||||
|
||||
Implementation: `get_or_create_notebook` would first find/create the provider
|
||||
notebook, then find/create the project notebook as a child.
|
||||
|
||||
---
|
||||
|
||||
## Token Expiry Notifications (future)
|
||||
## Token Expiry Notifications
|
||||
|
||||
Proactively warn when a token is close to expiry (within 48h for ChatGPT),
|
||||
rather than only surfacing the warning at startup. Options:
|
||||
@@ -165,9 +381,10 @@ rather than only surfacing the warning at startup. Options:
|
||||
- Send a desktop notification via `notify-send` (Linux) or `osascript` (macOS)
|
||||
when a token is within 24h of expiry
|
||||
|
||||
---
|
||||
Largely superseded by Brave cookie auto-extraction (#2): once refresh is
|
||||
one command (or automatic), expiry warnings matter much less.
|
||||
|
||||
## Search Command (future)
|
||||
## Search Command
|
||||
|
||||
Add a `search` command to full-text search across all exported Markdown files:
|
||||
|
||||
|
||||
Reference in New Issue
Block a user