- name
- chatgpt-import
- description
- Import ChatGPT conversation history into OpenClaw's memory search. Use when migrating from ChatGPT, giving OpenClaw access to old conversations, or building a searchable archive of past chats.
ChatGPT History Import
Import your ChatGPT conversations into OpenClaw so they're searchable via memory search.
Workflow
1. Export from ChatGPT
Follow references/export-guide.md to download your conversations.json.
2. Convert to Markdown
python3 scripts/convert_chatgpt.py \
--input /path/to/conversations.json \
--output /path/to/chatgpt-historyOptions: --min-messages N to skip trivial conversations (default: 2).
3. Embed into SQLite
export OPENAI_API_KEY=sk-...
python3 scripts/bulk_embed.py \
--history-dir /path/to/chatgpt-history \
--db /path/to/chatgpt-memory.sqliteOptions: --model, --batch-size, --max-workers, --chunk-size, --api-key.
4. Configure OpenClaw
Add as an extra search path in your OpenClaw config:
memorySearch:
extraPaths:
- /path/to/chatgpt-memory.sqliteThen restart the gateway:
openclaw gateway restartImportant Notes
- OpenAI API key required. The embed script sends conversation text to
api.openai.comfor embedding. If your conversations contain secrets, consider filtering them out first or using a scoped API key. - No key material stored. The generated DB does not store your API key.
- Back up first. The embed script will refuse to overwrite an existing output DB.
- Embeddings cost money — but it's cheap. ~2,400 conversations cost ~$0.15 with
text-embedding-3-small.