tulving 0.0.1

The context-budget engine for AI agents — persistent typed memory with token-budget curation. Name-holding pre-release; v0.1 in active development.

Tulving

The context-budget engine for AI agents.

Status: pre-release (0.0.1) — name-holding release; v0.1 is in active development.

Tulving is a model-agnostic Python SDK that gives an AI agent persistent, structured, searchable working memory — and, as its headline capability, curates that memory back into a fixed token budget:

ctx = memory.curate("resuming work on the auth refactor", token_budget=4000)

Named after Endel Tulving, the psychologist who established that memory has types (episodic vs semantic). Typed memories — facts, decisions, observations, plans, summaries, each with its own lifecycle — are Tulving's core data model.

What v0.1 will ship

• Core memory engine — store / get / semantic search over typed memories; zero infrastructure (one SQLite file, local vectors optional, no API key required)
• Token-budget context curation — curate(query, token_budget) selects, ranks, and trims memories into a prompt-ready block; orient mode for cold starts
• Lazy decay & eviction — importance fades per-type over time; decisions never decay; nothing is destroyed, only archived
• Sessions — per-agent session tracking, end-of-session summarization, abandoned-session recovery
• MCP server — six tools for Claude Code and other MCP clients, with single-writer safety
• Adapters & export — pluggable embeddings/LLM, JSON round-trip export

By the same author: Kairos (kairos-ai) — contract-enforced AI workflows. A kairos-ai-tulving integration plugin is planned.

License

TBD (MIT or Apache 2.0) — will be finalized with the v0.1 release.