AIChatExporter/README.md

# AI Chat Exporter

A personal backup tool for ChatGPT and Claude conversation history. Exports your chats to Markdown files and syncs them to [Joplin](https://joplinapp.org/) as notes. Each conversation becomes a single `.md` file with YAML frontmatter, organised into folders that map directly to Joplin notebooks.

Supports incremental sync — only new or updated conversations are exported on each run. Every run is resumable: if interrupted, re-running picks up exactly where it left off.

---

## ⚠️ Terms of Service Warning

**Read this before using this tool.**

This tool works by accessing **unofficial, undocumented internal web API endpoints** used by the ChatGPT and Claude web apps. These endpoints are not publicly supported by OpenAI or Anthropic and are subject to change or removal without notice.

**Use of this tool may conflict with their Terms of Service:**
- OpenAI: https://openai.com/policies/terms-of-use
- Anthropic: https://www.anthropic.com/legal/consumer-terms

**By using this tool, you accept that:**
- You are using it entirely at your own risk
- Your account could potentially be suspended for automated or scripted access
- The internal APIs this tool relies on may break at any time without notice
- This tool is for **personal archival use only** — not commercial use

This tool is designed for a single user backing up their own conversations. Do not use it to scrape data at scale or for any commercial purpose.

---

## Installation

### Linux / macOS

```bash
git clone <repo-url>
cd AIChatExporter
./ai-chat-exporter doctor
```

That's the whole install. The `ai-chat-exporter` wrapper creates `.venv` and
installs dependencies on first run, and reinstalls whenever `pyproject.toml`
changes — so there is no `python3 -m venv` / `source .venv/bin/activate` to
remember, on this machine or the next one you clone onto. Every command in this
README works the same way:

```bash
./ai-chat-exporter export --provider all
./ai-chat-exporter sync
```

The wrapper does **not** change directory: `.env`, `cache/` and `exports/` all
resolve against your current directory, which is what lets one checkout archive
different machines into different places. Run it from the repo. (It warns if you
don't, because a different working directory means a different `cache/manifest.json`
— which would re-export everything and orphan your existing Joplin notes.)

Prefer the traditional route, or want the test dependencies? That still works:

```bash
python3 -m venv .venv && source .venv/bin/activate && pip install -e ".[dev]"
```

### Windows

No admin access required. Run these in **Command Prompt** (`cmd.exe`) — it's the simplest option on Windows because it doesn't have PowerShell's script execution policy restrictions.

```bat
git clone <repo-url>
cd AIChatExporter
ai-chat-exporter doctor
```

`ai-chat-exporter.cmd` does the same bootstrap as the POSIX wrapper — it creates
`.venv` and installs dependencies on first run. No `python -m venv`, no
`.venv\Scripts\activate`.

**How you invoke it differs between the two Windows shells:**

| Shell | Command |
|---|---|
| Command Prompt (`cmd.exe`) | `ai-chat-exporter export --provider all` |
| PowerShell | `.\ai-chat-exporter.cmd export --provider all` |

`cmd.exe` searches the current directory before `PATH` and resolves the bare name
through `PATHEXT`, so it finds `ai-chat-exporter.cmd` with no prefix and no
extension. PowerShell deliberately does *not* search the current directory, and
`.\ai-chat-exporter` there would resolve to the extensionless POSIX script, which
PowerShell cannot execute — so name the `.cmd` explicitly. Command Prompt is the
simpler of the two here.

All `ai-chat-exporter` commands work identically in Command Prompt.

**Using PowerShell instead?** If you prefer PowerShell, you may need to allow script execution first (one-time, current user only):

```powershell
Set-ExecutionPolicy RemoteSigned -Scope CurrentUser
```

Then activate the venv and run commands the same way.

**Prerequisites:**
- Python 3.11 or later — install from [python.org](https://www.python.org/downloads/windows/). During installation, tick **"Add Python to PATH"**.
- Git — install from [git-scm.com](https://git-scm.com/) if not already present.

**Notes:**
- The cache manifest and logs are stored in `cache\` inside the install directory — the same as on Linux.
- File permission hardening (`chmod 600`) is silently ignored on Windows — not a concern for single-user desktop use.
- Joplin Web Clipper runs on `localhost:41184` on all platforms; no configuration changes needed.

---

## First Run: Run Doctor

Before anything else, validate your setup:

```bash
ai-chat-exporter doctor
```

This checks token presence, format, token health (via the `/api/auth/session` `error` field), directory permissions, disk space, and live API connectivity. Fix any failures before proceeding.

### Checking for API drift

The exporter reads ChatGPT's and Claude's undocumented internal web APIs, which can change shape without notice. The worst failure for a backup tool is *silent* — a response change that makes the exporter skip or mis-parse content without erroring. Run the canary to catch that early:

```bash
ai-chat-exporter canary
```

It probes one conversation per provider and checks only the fields the parser depends on (a renamed retrieval-tool author that would bypass the content-collapse, a new content type, drifted message fields, ignored attachments). `OK` means the live schema still matches; `WARN`/`ERROR` tells you exactly what changed. Worth running before a large export or on a schedule.

---

## Getting Your Session Tokens

Session tokens are how your browser stays logged in. This tool uses them to access your chat history on your behalf.

Tokens are entered manually — copy them from your browser's DevTools and run the wizard:

```bash
ai-chat-exporter auth
```

The wizard detects your OS, shows the correct DevTools shortcut, and writes the values to `.env` without echoing them to the terminal.

> **Why no auto-extraction from the browser?** Modern Chromium browsers (Chrome 127+, current Brave) encrypt cookies on Windows with **App-Bound Encryption**: the key is bound to the browser through a SYSTEM-level service, so reading cookies off disk requires Administrator rights and a PsExec-style SYSTEM impersonation that antivirus flags as credential theft — and it still fails on Brave specifically. There is no reliable, non-invasive way to pull these cookies automatically, so the manual DevTools flow below is the supported path.

### Token Lifetimes

| Provider | Cookie Name | Lifetime | Expiry Detection |
|----------|-------------|----------|-----------------|
| ChatGPT | `__Secure-next-auth.session-token.0` + `.1` | refresh ~weekly | `error` field of `/api/auth/session` — `doctor` reports "ChatGPT token active". The token is an encrypted JWE, so its `exp` is **not** readable client-side, and the `expires` field is a misleading rolling window; the `error` (`RefreshAccessTokenError` when dead) is the honest signal. |
| Claude | `sessionKey` | ~30 days | Opaque token — only detectable via 401 response |

### Finding Tokens in Chrome DevTools

1. Open the provider's website and make sure you're logged in
2. Press **F12** (Windows/Linux) or **Cmd+Option+I** (macOS) to open DevTools
3. Click the **Application** tab
4. In the left panel, expand **Cookies** and click the site URL
5. Find the cookie by name and copy its **Value**

**ChatGPT:** go to `https://chatgpt.com` → find **two** cookies:
- `__Secure-next-auth.session-token.0` — copy Value (starts with `eyJ`) → `CHATGPT_SESSION_TOKEN`
- `__Secure-next-auth.session-token.1` — copy Value → `CHATGPT_SESSION_TOKEN_1`

ChatGPT splits large session tokens across two cookies to stay under the browser's 4KB cookie limit. Both are required.

**Claude:** go to `https://claude.ai` → find `sessionKey` → copy Value

### When Tokens Expire

When a token expires you'll see a `401 Unauthorized` error. To refresh:
- Re-run the `auth` wizard: `ai-chat-exporter auth`
- Or manually update the value in your `.env` file

---

## The `auth` Command

The easiest way to configure tokens is the interactive wizard:

```bash
ai-chat-exporter auth
```

This walks you through finding your token, validates it, shows the expiry date (ChatGPT only), and offers to write it to your `.env` automatically. Tokens are never echoed to the terminal.

---

## `.env` Setup

Copy `.env.example` to `.env` and fill in your values:

```bash
cp .env.example .env
```

### Provider tokens

| Variable | Description |
|----------|-------------|
| `CHATGPT_SESSION_TOKEN` | ChatGPT session token chunk `.0` (starts with `eyJ…`) |
| `CHATGPT_SESSION_TOKEN_1` | ChatGPT session token chunk `.1` (the remainder) |
| `CHATGPT_PROJECT_IDS` | Comma-separated ChatGPT project IDs (see below) |
| `CLAUDE_SESSION_KEY` | Your Claude session key |

### Output

| Variable | Default | Description |
|----------|---------|-------------|
| `EXPORT_DIR` | `./exports` | Where to write exported Markdown files |
| `OUTPUT_STRUCTURE` | `provider/project/year` | Folder structure (see below) |
| `EXPORTER_HIDDEN_CONTENT` | `placeholder` | What to do with content invisible in the provider's web UI (file-retrieval tool dumps, Custom Instructions): `placeholder` collapses to a one-line note with size, `full` keeps everything, `omit` drops it. Dumps can be 90% of a conversation's bytes. |
| `EXPORTER_DOWNLOAD_MEDIA` | `images` | Download conversation assets into a `media/` folder beside each export and inline them: `images` (images only), `all` (also audio/voice clips), `off` (text placeholders only). Downloaded media is uploaded to Joplin as resources on the next `joplin` run. |
| `MAX_CONVERSATIONS_PER_RUN` | unlimited | Cap downloads per export run (per provider). Runs are resumable, so re-running continues where the cap stopped — useful to spread a large first export across several sessions. |
| `REQUEST_DELAY` | `1.0` | Seconds between consecutive API requests, with small random jitter, so traffic stays human-paced. Set `0` to disable. |

### Joplin

| Variable | Default | Description |
|----------|---------|-------------|
| `JOPLIN_API_TOKEN` | — | Authorization token from Joplin Web Clipper settings |
| `JOPLIN_API_URL` | `http://localhost:41184` | Joplin API URL (change only if you've customised the port) |
| `JOPLIN_REQUEST_TIMEOUT` | `30` | Seconds before an API call times out. Increase for very large conversations. |

### Cache & logging

| Variable | Default | Description |
|----------|---------|-------------|
| `CACHE_DIR` | `./cache` | Where to store the sync manifest |
| `LOG_FILE` | `./cache/logs/exporter.log` | Log file path (`none` to disable) |

---

## ChatGPT Projects

ChatGPT project conversations are stored separately from your main conversation list and require extra configuration.

### Finding your project IDs

The quickest way is to let the exporter find them:

```
ai-chat-exporter projects
```

It lists every project your conversations actually belong to, marks which are
missing from `.env`, and prints a paste-ready `CHATGPT_PROJECT_IDS=` line
(`--write` updates `.env` for you). If your ChatGPT account does not include
the project on conversation summaries, add `--deep` and it reads each
conversation's detail instead — slower, one request per conversation, but
complete.

Why it matters: project attribution is resolved from each conversation's own
`gizmo_id`, so exports file correctly whether or not a project is configured.
But the *listing* pass still needs `CHATGPT_PROJECT_IDS` — conversations that
live only inside a project never appear in the default conversation list, so an
unlisted project's chats are never fetched at all. Every export run also names
any unconfigured project it encounters.

To find them by hand instead:

1. Open ChatGPT and click a Project in the left sidebar
2. Look at the browser URL — it will look like:
   `https://chatgpt.com/g/g-p-68c2b2b3037c8191890036fb4ae3ed9f-my-project/project`
3. Copy the `g-p-…` part (everything up to but not including the slug after the second `-`)

Add all your project IDs to `.env` as a comma-separated list:

```
CHATGPT_PROJECT_IDS=g-p-68c2b2b3037c8191890036fb4ae3ed9f,g-p-anotherprojectid
```

The `auth` wizard can also guide you through this step interactively.

---

## Claude Code Sessions

The `claude-code` provider archives your local [Claude Code](https://claude.com/claude-code) agent transcripts — no tokens, no API, no ToS exposure. Sessions are read from `~/.claude/projects/`.

```bash
ai-chat-exporter export --provider claude-code
ai-chat-exporter joplin --provider claude-code
```

Exports are prose-only by default: your prompts and Claude's write-ups are kept, tool activity is grouped into one-line placeholders (`> 🔧 Tool output — 14 calls: Read ×9, Bash ×2 (86KB) — omitted`), and internal reasoning is dropped (counted in the run summary). Set `EXPORTER_HIDDEN_CONTENT=full` to keep everything. Sessions become notes under their own top-level **`AI-ClaudeCode`** Joplin notebook, in a sub-notebook per launch folder. The provider is included in `--provider all` whenever a sessions directory exists.

**Subagents.** Claude Code stores subagent (Task-tool) transcripts as separate files under `<session>/subagents/`; each is folded into its parent session inline, as a collapsible `<details>` block labeled with the subagent's type and description (its own tool traffic is collapsed like the main dialogue).

**Repo tags.** Sessions launched from a workspace root all share one folder-named notebook, so titles carry the repos each session touched — `Resume StartWRT project work [start-technologies]` — for at-a-glance scanning and search. A file's repo is the git repository it lives in (nearest ancestor with a `.git`), resolved from the tool paths in the transcript, so work is tagged wherever it happened — even across workspaces — and config/one-off files are ignored (they aren't repos). Repos are frequency-ordered and capped at 3. To never tag specific repos, set `CLAUDE_CODE_REPO_TAG_IGNORE` (comma-separated). Note this reads your current git layout, so a repo you later delete or move drops from the tag on re-export.

**Multiple locations.** By default the provider scans `~/.claude/projects/` plus `$CLAUDE_CONFIG_DIR/projects` when `CLAUDE_CONFIG_DIR` is set. To scan additional roots (e.g. other machines' sessions copied onto this box), set `CLAUDE_CODE_DIR` to a `:`-separated list:

```bash
CLAUDE_CODE_DIR="$HOME/.claude/projects:/mnt/backup/laptop/.claude/projects"
```

Sessions from all roots are merged by folder (no per-machine label); if the same session UUID appears in two roots, the newer copy wins. Note the exporter only sees this machine's disk and cannot recover sessions Claude Code has already pruned — run it regularly.

---

## Codex Sessions

The `codex` provider archives your local [Codex CLI](https://chatgpt.com/codex) agent transcripts — same deal as Claude Code: no tokens, no API, no ToS exposure. Rollout files are read from `~/.codex/sessions/YYYY/MM/DD/rollout-*.jsonl`.

```bash
ai-chat-exporter export --provider codex
ai-chat-exporter joplin --provider codex
```

Exports are prose-only by default, with the same placeholder format as Claude Code, into their own top-level **`AI-Codex`** Joplin notebook. Repo tags work the same way (`CODEX_REPO_TAG_IGNORE` to suppress), and additional roots can be scanned with `CODEX_DIR` (`:`-separated); `CODEX_HOME`'s `sessions/` is picked up automatically when that variable is set.

Three things differ from Claude Code, all forced by how Codex stores its data:

**Reasoning cannot be exported.** Codex encrypts it at rest — every reasoning record carries `encrypted_content` with no plaintext summary in any layer of the file. It is always dropped and counted; `EXPORTER_HIDDEN_CONTENT=full` cannot bring it back.

**Incomplete tool calls are reported.** Codex writes each session twice in one file: its own typed items (what actually ran) and the raw model-facing wire format (everything attempted). The provider reads the typed layer — it is already decoded, and it omits harness plumbing that would otherwise need stripping — but cross-checks the raw layer for calls that never produced a result, so placeholders read `3 calls: exec_command ×3 (+2 did not complete)`. Those are commands that failed to launch, that you aborted, or that were still running when the turn ended.

**Cloud tasks are out of scope.** `codex cloud` tasks run server-side and are reachable at `chatgpt.com/backend-api/api/codex/tasks`, but local CLI sessions are never uploaded there, so the cloud API is not an alternative source for these transcripts and this provider stays entirely offline. If you start using `codex cloud exec`, those transcripts would be cloud-only and would need separate work.

---

## Scheduling a Daily Run

`sync` chains `export` then `joplin` in one invocation, which is what a scheduler
wants — one command, and a meaningful exit code so a failed run is visible
instead of silent.

```bash
./ai-chat-exporter sync                      # every configured provider
./ai-chat-exporter sync --provider codex     # just one
```

### Linux (systemd user timer)

```bash
./scheduling/install-systemd-timer.sh --provider claude-code --provider codex
./scheduling/install-systemd-timer.sh --uninstall
```

Defaults to 09:00 daily (`--time 21:30` to change). `Persistent=true` means a
machine that was off at the scheduled time runs the archive at next boot rather
than skipping the day. To archive while logged out, `loginctl enable-linger $USER`.

Check on it with `systemctl --user list-timers aichat-sync.timer` and
`journalctl --user -u aichat-sync.service -n 50`.

### Windows (Task Scheduler)

```powershell
.\scheduling\Register-AiChatSyncTask.ps1 -Provider chatgpt,claude
.\scheduling\Register-AiChatSyncTask.ps1 -Unregister
```

Per-user task, no admin rights needed. `-StartWhenAvailable` is the counterpart
of systemd's `Persistent=true`.

### What to know before you rely on it

**List only the providers that work unattended on that machine.** The local
providers (`claude-code`, `codex`) need no credentials and always work. The web
providers depend on a session token that expires and can only be refreshed by
hand via DevTools — so on a machine where that token is stale, scheduling them
means a failed run every single day, which is a good way to learn to ignore
failures you actually want to see. That is why `--provider` is repeatable in both
installers: schedule the coding machine for `claude-code` + `codex`, the browser
machine for `chatgpt` + `claude`.

**Both installers pass `--joplin-optional`.** If Joplin desktop isn't running,
the sync warns instead of failing: the export has already captured the local
transcripts (the part that can disappear), and the notes are rebuilt from the
cache on the next run that finds Joplin up.

**One provider failing does not skip the rest.** Both installers loop over the
providers in a single action rather than one action each, because systemd
`oneshot` stops at the first failing `ExecStart` and Task Scheduler reports only
the last action's result. Every provider is attempted; the run still exits
non-zero if any failed.

**Acknowledge the ToS notice once, interactively.** It's stored in the cache
manifest per machine. Until then a scheduled run exits 1 with an explanation
rather than hanging on a prompt no one can answer.

---

## Output Structure

All exported files go under `EXPORT_DIR`. The folder structure maps directly to Joplin notebooks.

### Default: `provider/project/year`

```
exports/
├── chatgpt/
│   ├── no-project/
│   │   └── 2024/
│   │       └── 2024-03-15_my-conversation_abc12345.md
│   └── learning-python/
│       └── 2024/
│           └── 2024-03-15_async-tutorial_def67890.md
└── claude/
    ├── no-project/
    │   └── 2024/
    │       └── 2024-06-01_docker-explained_ghi11111.md
    └── startos-packaging/
        └── 2024/
            └── 2024-06-10_manifest-setup_jkl22222.md
```

### Joplin Notebook Mapping

Each provider+project combination maps to a flat Joplin notebook created automatically by the `joplin` command:

| Export folder | Joplin notebook |
|---------------|-----------------|
| `exports/chatgpt/learning-python/` | `ChatGPT - Learning Python` |
| `exports/claude/startos-packaging/` | `Claude - Startos Packaging` |
| `exports/chatgpt/no-project/` | `ChatGPT - No Project` |
| `exports/claude/no-project/` | `Claude - No Project` |

### Other `OUTPUT_STRUCTURE` options

| Value | Result |
|-------|--------|
| `provider/project/year` (default) | `exports/claude/my-project/2024/file.md` |
| `provider/project` | `exports/claude/my-project/file.md` |
| `provider/year` | `exports/claude/2024/file.md` (projects ignored) |

### Filename format

`YYYY-MM-DD_{title-slug}_{id[:8]}.md` — e.g. `2024-06-10_manifest-setup_jkl22222.md`

---

## CLI Reference

### Global flags

```
--verbose / -v     DEBUG output to console
--quiet / -q       WARNING and above only
--debug            DEBUG + full tracebacks + redacted API response bodies
--no-log-file      Disable file logging
--version          Print version and exit
```

### `auth` — Interactive token setup

```bash
ai-chat-exporter auth                  # manual wizard (DevTools flow)
```

Guided wizard to find and save session tokens and ChatGPT project IDs. Detects OS and shows the correct DevTools shortcut, then writes the values to `.env`.

### `doctor` — Health check

```bash
ai-chat-exporter doctor
```

Checks: token presence, JWT validity and expiry, directory permissions, disk space, live API reachability. Exits with code 0 if all pass, 1 if any fail.

### `export` — Export conversations

```bash
# Export everything (new/updated only)
ai-chat-exporter export

# Single provider
ai-chat-exporter export --provider claude

# JSON output
ai-chat-exporter export --format json

# Both Markdown and JSON
ai-chat-exporter export --format both

# Only conversations updated since a date
ai-chat-exporter export --since 2024-06-01

# Only conversations in a specific project (case-insensitive substring)
ai-chat-exporter export --project "learning python"

# Only conversations outside any project
ai-chat-exporter export --project none

# Write to a custom directory
ai-chat-exporter export --output /path/to/my/notes

# Preview without writing anything
ai-chat-exporter export --dry-run
```

Options: `--provider [chatgpt|claude|claude-code|codex|all]`, `--format [markdown|json|both]`, `--output PATH`, `--since YYYY-MM-DD`, `--project NAME`, `--hidden-content [full|placeholder|omit]`, `--download-media [images|all|off]`, `--max-conversations N`, `--force`, `--dry-run`

**Re-rendering the whole archive after an upgrade.** New formatting or features (collapse policy, media downloads) only change conversations as they're re-exported. To re-render everything you already have, use `--force` — it re-exports every conversation even if unchanged, **without** `cache --clear`, so your Joplin note links are preserved (a later `joplin` run updates the existing notes instead of duplicating them).

A force re-render runs as a tracked "campaign": each run re-renders the least-recently-exported conversations, the "still to go" count shrinks each run, and finished providers do no further work. The simplest approach is one uncapped pass:

```bash
ai-chat-exporter export --force      # re-renders everything in one paced pass
ai-chat-exporter joplin              # update notes + upload media
```

Or spread the load with `--max-conversations`, re-running until it reports "Force re-render complete":

```bash
ai-chat-exporter export --force --max-conversations 50   # repeat until complete
```

### `list` — List conversations

```bash
# List all conversations for all providers
ai-chat-exporter list

# Single provider
ai-chat-exporter list --provider chatgpt

# Filter by project
ai-chat-exporter list --project "learning python"

# Only conversations outside any project
ai-chat-exporter list --project none
```

Fetches and displays all conversations without exporting them. Useful for verifying what the tool can see before running an export.

### `joplin` — Sync to Joplin

```bash
# Sync all pending conversations to Joplin
ai-chat-exporter joplin

# Preview what would be synced without sending anything
ai-chat-exporter joplin --dry-run

# Sync a single provider
ai-chat-exporter joplin --provider chatgpt

# Sync only conversations in a specific project
ai-chat-exporter joplin --project "learning python"

# Sync only conversations outside any project
ai-chat-exporter joplin --project none
```

Reads the local export cache and pushes each exported Markdown file to Joplin as a note. Notebooks are created automatically. Re-running is safe — notes are updated (not duplicated).

**Prerequisites:**
1. Run `export` first to generate the Markdown files
2. Open Joplin → Tools → Options → Web Clipper → enable the service
3. Copy the Authorization token and add `JOPLIN_API_TOKEN=<token>` to your `.env`
4. Joplin desktop must be open when you run this command

Options: `--provider [chatgpt|claude|all]`, `--project NAME`, `--dry-run`

### `prune` — Delete stale export files

```bash
# Preview what would be deleted
ai-chat-exporter prune --dry-run

# Delete (asks for confirmation; -y skips the prompt)
ai-chat-exporter prune
```

Deletes export files no longer referenced by the cache manifest — leftovers
from old folder layouts or fixed bugs that would otherwise double-sync into
Joplin. Refuses to run when the manifest is empty (e.g. right after
`cache --clear`) so it can never wipe a freshly cleared archive. The `doctor`
command separately verifies that every manifest entry's file exists on disk.

### `cache` — Manage the sync manifest

```bash
# Show statistics
ai-chat-exporter cache --show

# Clear all cached entries (forces full re-export next run)
ai-chat-exporter cache --clear

# Clear a single provider
ai-chat-exporter cache --clear --provider claude
```

---

## How the Cache Works

The cache manifest lives at `cache/manifest.json` (inside the install directory) and records every exported conversation: its title, project, `updated_at` timestamp, output file path, and (after Joplin sync) the Joplin note ID.

On every `export` run:
1. Fetch the full conversation list from the provider
2. Compare each conversation's `updated_at` against the manifest
3. Export only conversations that are new or have been updated
4. Write each successfully exported conversation to the manifest **immediately** (not batched)

On every `joplin` run:
1. Read the manifest to find conversations not yet synced to Joplin, or re-exported since last sync
2. Push each pending Markdown file to Joplin (create or update)
3. Store the Joplin note ID in the manifest so subsequent runs update rather than duplicate

**This design makes every run inherently resumable.** If the tool is interrupted for any reason — rate limit, network drop, Ctrl+C, crash — simply re-run the same command. It will skip already-processed conversations and continue from where it stopped.

To force a full re-export: `ai-chat-exporter cache --clear` then re-run export.

---

## Troubleshooting

### `401 Unauthorized`
Your session token has expired.
- Run `ai-chat-exporter auth` to get a new token interactively
- Or manually copy a fresh cookie value into your `.env` file

Note: Claude's `sessionKey` is an opaque string — the only way to know it's expired is the 401 error. ChatGPT JWTs have an `exp` claim that the `doctor` command can decode and display.

### `429 Rate Limited`
The tool automatically pauses, saves progress, and exits with a clear message showing how many conversations were exported vs remaining. Just re-run the same export command to resume — the cache picks up exactly where it left off.

### Joplin: "JOPLIN_API_TOKEN is not set"
You need to configure the token before running the `joplin` command:
1. Open Joplin desktop
2. Go to Tools → Options → Web Clipper
3. Enable the Web Clipper service
4. Copy the Authorization token shown on that page
5. Add `JOPLIN_API_TOKEN=<token>` to your `.env` file

### Joplin: "Joplin is not responding"
Joplin desktop must be running when you run the `joplin` command. The Web Clipper service shuts down when Joplin is closed.

### Joplin: "Joplin rejected the API token (HTTP 401)"
The token in `JOPLIN_API_TOKEN` doesn't match what Joplin expects. Get a fresh token from Joplin → Tools → Options → Web Clipper → Authorization token.

### Joplin: note timed out
If you see a timeout error, Joplin took longer than `JOPLIN_REQUEST_TIMEOUT` seconds (default: 30) to respond. Possible causes:
- The conversation is very large and Joplin is slow to index it
- Joplin is busy syncing or loading a large library
- Joplin has frozen — try restarting it

To increase the timeout: add `JOPLIN_REQUEST_TIMEOUT=60` to your `.env`.

### ChatGPT project conversations not appearing
Make sure you've added the project IDs to `CHATGPT_PROJECT_IDS` in your `.env`. See [ChatGPT Projects](#chatgpt-projects) for how to find them. Project conversations are not included in the default conversation listing — they must be fetched separately.

### Schema warnings in logs (`Unexpected API response shape`)
The provider's internal API may have changed. Run with `--debug`, sanitize the output (remove any personal content), and check the project's GitHub Issues for known fixes.

### Non-text content warnings
Since v0.4.0, rich content is preserved as typed blocks in the export. ChatGPT voice transcripts render as text and audio assets as `📎 File attached` placeholders with size and duration metadata. Anything the extractor doesn't recognise renders as a visible `> ⚠️ Unsupported content` block naming the type and observed keys, *and* increments a counter in the post-export summary so you can tell whether real content is being silently skipped.

### Embedded images and media
Since v0.6.0, image attachments are downloaded by default into a `media/` folder beside each export and inlined as `![](media/…)`. Audio and other files download only with `EXPORTER_DOWNLOAD_MEDIA=all`. On the next `joplin` run these are uploaded as Joplin resources so they render inside the note. Assets that have expired on the provider's side (older AI-generated images often do) keep their text placeholder and are tallied as `media failed` in the run summary — they're never fatal to the export. Set `EXPORTER_DOWNLOAD_MEDIA=off` to skip downloads entirely.

### Tool output / hidden context collapsed
Since v0.6.0, content that was invisible in the ChatGPT web UI is collapsed by default to one-line placeholders like `> 🔧 Tool output — file_search (15.0 KB) — omitted`. This is ChatGPT's file-retrieval tool re-injecting your attached files on every run — it can be 90% of a conversation's bytes while containing none of the dialogue. Custom Instructions collapse the same way (`> ℹ️ Hidden context`). The post-export summary lists every collapsed message by origin with the total KB omitted. To keep everything, set `EXPORTER_HIDDEN_CONTENT=full` in `.env` or pass `--hidden-content full`.

### Empty export / all conversations skipped
No new or updated conversations since your last run. To verify: `ai-chat-exporter cache --show`. To force a full re-export: `ai-chat-exporter cache --clear`.

### Filing a bug report
1. Run with `--debug`: `ai-chat-exporter export --debug 2>&1 | tee debug.log`
2. Remove any personal conversation content from `debug.log`
3. Open a GitHub Issue with the sanitized log and the exact command you ran

---

## Future Work

See `FUTURE.md` for the full roadmap. Current priorities:

- **Watch/scheduled mode** on the way to a headless StartOS service

---

## Security Notes

- All exported data is stored **locally only** — nothing is sent anywhere except to your local Joplin instance
- Exported files and the cache manifest are created with `600` permissions (owner read/write only)
- `.env` is in `.gitignore` — **never commit it**
- Session tokens are never logged, printed, or included in error messages
- The Joplin API token is only ever sent to `localhost` — it never leaves your machine
- If you accidentally commit `.env`: immediately log out and back in to invalidate the token, then remove it from git history using [BFG Repo Cleaner](https://rtyley.github.io/bfg-repo-cleaner/) or `git filter-branch`