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Complete the consolidation pipeline: summaries -> profile + eras -> narrative.
- memory: eras table (per-month digests) + Era, summaries_by_month, store_era,
list_eras, recall_eras; narrative table + set/get_narrative
- lyra/era.py (lyra-era): groups session gists by the month the session occurred
(real timestamps) and map-reduces each month into a "what was happening" digest
- lyra/narrative.py (lyra-narrative): distills profile + recent eras into the
current arc/trends/callbacks ("remember when…", "you're trending toward…")
- chat.build_messages injects the narrative alongside the profile
Verified on the real corpus: 17 monthly eras (Dec 2024-Jun 2026) + a narrative
that surfaces specific callbacks (the $573 Hollywood session, 4 years sober).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
84 lines
3.0 KiB
Python
84 lines
3.0 KiB
Python
"""Era rollups: per-month "what was happening" digests (consolidation step 3).
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Groups session gists by the calendar month the session occurred (from real
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exchange timestamps) and map-reduces each month into one digest. These are the
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temporal memory tier — they answer "what was going on last December" and feed
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the narrative engine. Runs on the consolidation backend (MI50 in steady state).
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"""
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from __future__ import annotations
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from lyra import config, llm, logbus, memory
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from lyra.llm import Backend, Message
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BATCH_CHARS = 18000
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_PROMPT = """You are writing a monthly memory digest about Brian from the session \
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summaries below (all from the same month). Capture: what he was focused on (poker \
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and otherwise), notable events/results/decisions, recurring themes, and his mood \
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and arc across the month. Third person, referring to him as "Brian". 5-10 \
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sentences. This is a memory record, not a reply. No preamble."""
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_MERGE_PROMPT = """Merge these partial monthly digests (same month) into one \
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coherent digest about Brian for that month. Keep it tight, 5-10 sentences, no \
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repetition. Third person."""
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def _batch_texts(texts: list[str], budget: int) -> list[str]:
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blocks, buf, size = [], [], 0
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for t in texts:
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if size + len(t) > budget and buf:
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blocks.append("\n\n".join(buf))
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buf, size = [], 0
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buf.append(t)
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size += len(t)
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if buf:
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blocks.append("\n\n".join(buf))
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return blocks
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def _call(prompt: str, body: str, backend: Backend) -> str:
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messages: list[Message] = [
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{"role": "system", "content": prompt},
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{"role": "user", "content": body},
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]
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return llm.complete(messages, backend=backend)
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def _digest_month(gists: list[str], backend: Backend) -> str:
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"""Map-reduce a month's session gists into one digest."""
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blocks = _batch_texts(gists, BATCH_CHARS)
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partials = [_call(_PROMPT, b, backend) for b in blocks]
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while len(partials) > 1:
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partials = [_call(_MERGE_PROMPT, g, backend) for g in _batch_texts(partials, BATCH_CHARS)]
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return partials[0]
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def rebuild_eras(backend: Backend | None = None) -> dict:
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"""(Re)build a digest for every month that has session gists."""
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backend = backend or config.load().summary_backend
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by_month = memory.summaries_by_month()
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months = 0
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for month in sorted(by_month):
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digest = _digest_month(by_month[month], backend)
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memory.store_era(month, digest, len(by_month[month]))
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months += 1
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logbus.log("info", "era built", month=month, sessions=len(by_month[month]))
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report = {"months": months}
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logbus.log("info", "eras complete", **report)
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return report
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def main() -> int:
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report = rebuild_eras()
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if not report["months"]:
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print("No summaries yet — run lyra-summarize first.")
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return 1
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for era in memory.list_eras():
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print(f"\n## {era.month} ({era.session_count} sessions)\n{era.content}")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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