ChatGPT Import

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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.

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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.