etot-core

Shared engine for ETOT agentic loops: a produce → check → revise controller, a structured Claude client, a run logger, and config loading. It knows nothing about any one tool's prompts, rules, or corpus — those live beside each tool that uses it.

Motif is the first tool built on it.

What's in it

etot_core/
    loop.py      generic plan -> act -> check -> revise -> stop controller
    llm.py       thin Claude client: one call, structured JSON out, usage tracked
    logger.py    per-run directory with every prompt, response, and metric saved
    config.py    load YAML config with model roles and critic rules

Install

pip install etot-core

Python 3.10+. Requires an Anthropic API key at call time (ANTHROPIC_API_KEY or a context-scoped key passed to core.llm).

A tool path that never calls a model can load its config without a key: load_config(path, require_key=False). The default (require_key=True) raises when no key is available.

Snapshots

RunLogger.snapshot_corpus(processed_dir, names) copies what a run reads into runs/<id>/corpus/, driven by processed_dir/manifest.json. Each entry needs a name; its files default to <name>.txt and <name>.jsonl, or it can list its own as "files": ["library.jsonl", ...]. A words count is recorded when every entry has one.

Use it in a new tool

from etot_core.loop import run_loop
from etot_core.logger import RunLogger
from etot_core import llm

result = run_loop(
    state,
    produce=produce,   # state -> state: first draft into state
    check=check,       # state -> verdict: {"pass": bool, "failures": [...]}
    revise=revise,      # state, verdict -> state: address failures
    max_iterations=3,
)

Call models through llm.call, log through RunLogger, and keep tool-specific prompts, rules, and corpus handling in your own package — etot_core never talks to a tool's domain, and a tool never re-implements the loop.

License

MIT. See LICENSE.