Open-source BabyCoder gives small local LLM agents a dreaming sleep loop that generates new questions
Illustrious_Matter_8 · reddit · 2026-09-30
A Reddit developer released BabyCoder, an MIT-licensed open-source toolkit for local agents running small models on 12GB VRAM or less (via LM Studio or any OpenAI-compatible server), after a major rewrite. Python owns the structure (files, memory, loop, rules) while the model only makes the next decision; on failed tool calls, Python suggests what was probably meant, keeping small models on track. Tested with Gemma 12B and Qwen models.
The new Lisa-agent runs continuously: she responds when spoken to, works on her own goals otherwise, gets tired and sleeps. During sleep she dreams about random memories, merges duplicates, and sometimes wakes with a question she researches the next day — e.g., after a conversation about the Dutch word "Herfst", she dreamed about seasons and words, woke wondering whether different words for one thing change its meaning, and independently found the Sapir-Whorf hypothesis.
Key differences from other sleeping-agent projects:
- Dreams produce questions, not answers, feeding back into the agent's own goals
- Readable, editable mind: plain-Markdown memory with merge archives (merged.md) for traceability, addressing concerns about Anthropic-style untraceable consolidation
- Dreams stay separate from memories to avoid echo chambers
- Small-model support: thinking guide, Wikipedia/web access while awake, and a bail-out after a few failed attempts instead of infinite loops
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