by brainless
AI enabled insights from emails, calendars, contacts, files, Slack, databases, web... Fast, private and local. Launching soon!
# Add to your Claude Code skills
git clone https://github.com/brainless/dwataConnect your email inbox, download emails, and use LLM agents to extract financial transaction data — all running locally on your machine.
All data stays on your machine. dwata works with Ollama and local models (tested on Mac Mini M4 16GB), so your emails never leave your computer.
[!WARNING] dwata is very early software and is being developed actively, I am sorry if the extracted data has bugs.
Connect your Gmail or IMAP account. dwata downloads your emails and stores them locally in SQLite.

Select financial emails and run an LLM agent to generate extraction templates. The agent reads sample emails and produces reusable patterns — you only need AI once per email sender.


Browse and manage the generated templates. Each template captures how to extract financial data from a specific sender.

Once templates are in place, dwata extracts financial transactions from matching emails automatically.
[!WARNING] There are quite a few issues with the extraction logic. I am working on it actively.


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Use Ollama with a local model (Ministral 3: 3b), OpenAI (GPT-4o Nano), or Google Gemini (Gemini 2.5 Flash Preview). Switch models in settings.

Download the latest release for your platform from GitHub Releases.
Run the dwata API server and open the GUI in your browser at http://localhost:3030.
dwata supports Gmail via OAuth. Set your Google OAuth client_id and client_secret in the config file:
~/Library/Application Support/dwata/project.toml~/.config/dwata/project.toml%APPDATA%\dwata\project.tomlYou can use your own Google OAuth app (bring-your-own credentials).
Install Ollama and pull model Ministral 3:3b:
ollama pull ministra...