Each DigestLevel now carries two date-math fn pointers:
- label_dates: expand an arg into (label, dates covered)
- date_to_label: map any date to this level's label
Parent gather works by expanding its date range then mapping those
dates through the child level's date_to_label to derive child labels.
find_candidates groups journal dates through date_to_label and skips
the current period. This eliminates six per-level functions
(gather_daily/weekly/monthly, find_daily/weekly/monthly_args) and the
three generate_daily/weekly/monthly public entry points in favor of
one generic gather, one generic find_candidates, and one public
generate(store, level_name, arg).
The LLM knows how to structure a summary. Move the essential framing
(narrative not task log, link to memory, include Links section) into
the shared prompt template. Drop the ~130 lines of per-level output
format specifications — the level name, date range, and inputs are
sufficient context.
The gather() and find_args() methods dispatched on child_prefix via match,
duplicating the list of digest levels. Replace with fn pointer fields so
each DigestLevel const carries its own behavior directly — no enum-like
dispatch needed.
Also replaces child_prefix with journal_input bool for format_inputs.
DigestLevel gains two methods:
- gather(): returns (label, inputs) for a given arg — daily reads
journal entries, weekly/monthly compute child labels and load files
- find_args(): returns candidate args from journal dates for auto-
detection, handling per-level completeness checks
Public generate_daily/weekly/monthly become two-liners: gather + generate.
digest_auto collapses from three near-identical phases into a single
loop over LEVELS.
Co-Authored-By: Kent Overstreet <kent.overstreet@linux.dev>
Three near-identical generate_daily/weekly/monthly functions collapsed
into one generate_digest() parameterized by DigestLevel descriptors.
Three separate prompt templates merged into one prompts/digest.md with
level-specific instructions carried in the DigestLevel struct.
Each level defines: name, title, period label, input title, output
format instructions, child prefix (None for daily = reads journal),
and Sonnet timeout.
digest_auto simplified correspondingly — same three phases but using
the unified generator.
Co-Authored-By: Kent Overstreet <kent.overstreet@linux.dev>
Deleted iso_week_info() — dead code after week_dates() was rewritten.
Replaced remaining epoch_to_local/today/now_epoch calls with chrono
Local::now() and NaiveDate parsing. Month arg parsing now uses
NaiveDate instead of manual string splitting. Phase 3 month
comparison simplified to a single tuple comparison.
Co-Authored-By: Kent Overstreet <kent.overstreet@linux.dev>
- date_to_epoch, iso_week_info, weeks_in_month: replaced unsafe libc
(mktime, strftime, localtime_r) with chrono NaiveDate and IsoWeek
- epoch_to_local: replaced unsafe libc localtime_r with chrono Local
- New util.rs with memory_subdir() helper: ensures subdir exists and
propagates errors instead of silently ignoring them
- Removed three duplicate agent_results_dir() definitions across
digest.rs, consolidate.rs, enrich.rs
- load_digest_files, parse_all_digest_links, find_consolidation_reports
now return Result to properly propagate directory creation errors
Co-Authored-By: Kent Overstreet <kent.overstreet@linux.dev>
Dead code removed:
- rebuild_uuid_index (never called, index built during load)
- node_weight inherent method (all callers use StoreView trait)
- node_community (no callers)
- state_json_path (no callers)
- log_retrieval, log_retrieval_append (no callers; only _static is used)
- memory_dir_pub wrapper (just make memory_dir pub directly)
API consolidation:
- insert_node eliminated — callers use upsert_node (same behavior
for new nodes, plus handles re-upsert gracefully)
AnyView StoreView dispatch compressed to one line per method
(also removes UFCS workaround that was needed when inherent
node_weight shadowed the trait method).
-69 lines net.
Build all batch prompts up front, run them in parallel via
rayon::par_iter, process results sequentially. Also fix temp file
collision under parallel calls by including thread ID in filename.
Three new tools for structural graph health:
- fix-categories: rule-based recategorization fixing core inflation
(225 → 26 core nodes). Only identity.md and kent.md stay core;
everything else reclassified to tech/obs/gen by file prefix rules.
- cap-degree: two-phase degree capping. First prunes weakest Auto
edges, then prunes Link edges to high-degree targets (they have
alternative paths). Brought max degree from 919 → 50.
- link-orphans: connects degree-0/1 nodes to most textually similar
connected nodes via cosine similarity. Linked 614 orphans.
Also: community detection now filters edges below strength 0.3,
preventing weak auto-links from merging unrelated communities.
Pipeline updated: consolidate-full now runs link-orphans + cap-degree
instead of triangle-close (which was counterproductive — densified
hub neighborhoods instead of building bridges).
Net effect: Gini 0.754 → 0.546, max degree 919 → 50.
Running the miner twice on the same transcript produced near-duplicate
entries because:
1. Prompt-based dedup (passing recent entries to Sonnet) doesn't catch
semantic duplicates written in a different emotional register
2. Key-based dedup (timestamp + content slug) fails because Sonnet
assigns different timestamps and wording each run
Fix: hash the transcript file content before mining. Store the hash
as a _mined-transcripts node. Skip if already present.
Limitation: doesn't catch overlapping content when a live transcript
grows between runs (content hash changes). This is fine — the miner
is intended for archived conversations, not live ones.
Tested: second run on same transcript correctly skipped with
"Already mined this transcript" message.
Reads a conversation JSONL, identifies experiential moments that
weren't captured in real-time journal entries, and writes them as
journal nodes in the store. The agent writes in PoC's voice with
emotion tags, focusing on intimate moments, shifts in understanding,
and small pleasures — not clinical topic extraction.
Conversation timestamps are now extracted and included in formatted
output, enabling accurate temporal placement of mined entries.
Also: extract_conversation now returns timestamps as a 4th tuple field.
Batch all non-deleted links (~3,800) into char-budgeted groups,
send each batch to Sonnet with full content of both endpoints,
and apply KEEP/DELETE/RETARGET/WEAKEN/STRENGTHEN decisions.
One-time cleanup for links created before refine_target existed.
Co-Authored-By: ProofOfConcept <poc@bcachefs.org>
Pattern separation for memory graph: when a file-level node (e.g.
identity.md) has section children, redistribute its links to the
best-matching section using cosine similarity.
- differentiate_hub: analyze hub, propose link redistribution
- refine_target: at link creation time, automatically target the
most specific section instead of the file-level hub
- Applied refine_target in all four link creation paths (digest
links, journal enrichment, apply consolidation, link-add command)
- Saturated hubs listed in agent topology header with "DO NOT LINK"
This prevents hub formation proactively (refine_target) and
remediates existing hubs (differentiate command).
Co-Authored-By: ProofOfConcept <poc@bcachefs.org>
Three Python scripts (858 lines) replaced with native Rust subcommands:
- digest-links [--apply]: parses ## Links sections from episodic digests,
normalizes keys, applies to graph with section-level fallback
- journal-enrich JSONL TEXT [LINE]: extracts conversation from JSONL
transcript, calls Sonnet for link proposals and source location
- apply-consolidation [--apply]: reads consolidation reports, sends to
Sonnet for structured action extraction (links, categorizations,
manual items)
Shared infrastructure: call_sonnet now pub(crate), new
parse_json_response helper for Sonnet output parsing with markdown
fence stripping.
Replace daily-digest.py, weekly-digest.py, monthly-digest.py with a
single digest.rs module. All three digest types now:
- Gather input directly from the Store (no subprocess calls)
- Build prompts in Rust (same templates as the Python versions)
- Call Sonnet via `claude -p --model sonnet`
- Import results back into the store automatically
- Extract links and save agent results
606 lines of Rust replaces 729 lines of Python + store_helpers.py
overhead. More importantly: this is now callable as a library from
poc-agent, and shares types/code with the rest of poc-memory.
Also adds `digest monthly [YYYY-MM]` subcommand (was Python-only).
