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How to answer questions from your own notes over WhatsApp with Wappy Kit

Ingest your notes into a local knowledge base and ask about them from WhatsApp, fully offline.

Who it is forA researcher or student who keeps notes and documents and wants grounded answers without uploading them anywhere.

The problemSearching personal notes is slow, and general chat models guess when they lack your material.

The outcomeA WhatsApp agent that answers from the documents you ingested and stays on your machine.

What you need first

  • Node.js 22 or newer
  • A WhatsApp Cloud API app from Meta's developer portal with a phone number, access token, and app secret
  • A model API key from OpenAI, Anthropic, or Gemini, or a local Ollama install
  • A Google account, only if you use the Gmail/Calendar assistant

Steps

  1. Run npm create @wappy_ai/agent and pick Local (SQLite/LibSQL) as the knowledge backend.
  2. Run cp .env.sample .env and add your model key and WhatsApp credentials.
  3. Run npm install.
  4. Ingest your notes or documents through the Knowledge layer in the generated project, since the README does not name the ingestion command. (inferred, check the README)
  5. Run npm run dev and ask a question about one of your documents from WhatsApp.

Prompt for your agent

In the csr1010/wappy-kit repo, scaffold a project with `npm create @wappy_ai/agent` into ./<project-dir> and choose the local knowledge backend. Expected output: a generated project with a Knowledge/RAG layer backed by SQLite/LibSQL. Verify that the knowledge backend setting in the generated config is local and that no external service URL is required.

Caveat. The local backend uses BM25 keyword matching, so it does not extract entities or relationships the way the Cognee option does.

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