---

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-history

Options: --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.sqlite

Options: --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.sqlite

Then restart the gateway:

openclaw gateway restart

Important Notes

• OpenAI API key required. The embed script sends conversation text to api.openai.com for 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.