Why It Hits Different
- Messaging-native architecture, not a browser dashboard in disguise.
- One assistant core across multiple frontends.
- Skills plus collectors for actions and live context.
BUDUCCA is a lightweight control plane for Telegram, Signal, WhatsApp, and Android assistants. Plug in a modern OpenAI-compatible model endpoint, wire up skills and collectors, and keep state in plain files instead of black-box cloud machinery.
The model layer speaks the OpenAI chat-completions protocol, so BUDUCCA fits cleanly behind local or remote open-model serving stacks.
Traces, collector outputs, unanswered messages, and learned context stay in a readable workspace. That keeps debugging, backup, diffing, and manual inspection straightforward when you need to see exactly what the assistant has stored. Audit trail included.
Small Python modules, direct config files, and no required hosted backend. The stack is easier to reason about because most changes happen close to the behavior they affect, without hidden orchestration or extra service glue. Fewer layers. Less drift. Faster edits.
Clone, point `llm.json` at your model endpoint, enable one frontend, then boot the relay.
cp -R config.example config
$EDITOR config/llm.json
$EDITOR config/telegram.json
python3 run_bot.py --config config
For open-model serving, start with LM Studio or Ollama's OpenAI-compatible API.