russell@unturf.com
856b3116d7
A content-addressed, Merkle-committed document store implementing the runtime spec from Merkle Providence Reverse RAG (April 2026 whitepaper) and Merkle-AGI v9.8 admissibility ledger. Ports proxy.unturf.com Go merkle conventions to Python: non-commutative HashCombine with 0x03 prefix, explicit IsLeft per sibling, self-duplicate odd elements. What's in: - merkle.py — proof generation/verification, JSON serialization - store.py — v9.8 SQLite schema: 8-dim providence_cache key, falsification_state, append-only audit chain, surface/core kind, hot/warm/cold tier, derivations, edges - ingest.py — Source -> normalize -> chunk -> merkle -> upsert, idempotent on document_root collision - search/ — SearchBackend ABC with explicit AuditMode (STRICT/HYBRID/ VISUAL), FTS5 backend returning VISUAL hits - sources/ — wikipedia.py (streaming bz2/MySQL extended-INSERT parser for 2003-era cur dumps); html_page.py (selectolax + httpx, robots.txt honored automatically) - distill/ — Distiller ABC + first-sentence-v1 stub. Runner generates per-contributing-chunk Merkle proofs binding cores back to source document_root. - evict.py — hot->cold demote (NULLs content, drops FTS row, retains leaf_hash). rehydrate() refetches via source pipeline; matching root restores content, mismatching root marks providence stale and writes rehydrate_drift event. Cores never evict. - cli.py — ingest / search / verify / stats / distill / evict / rehydrate - 31 tests covering merkle round-trip, ingest+audit, chunker version binding, html parse, distillation proof verification, evict+ rehydrate including drift detection. Smoke: 503 Wikipedia 2003-05-16 + 3 fox-owned HTML pages ingested, 478 cores produced (24 surface->core merkle dedups), 7 chunks evicted to cold and round-tripped via rehydrate, 987 audit events chained 0 breaks.
42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
"""Distiller ABC.
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A Distiller compresses a surface Document into a core Document. The runner
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generates Merkle proofs for every contributing source chunk so the resulting
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derivation row cryptographically binds the core back to its source.
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"""
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from __future__ import annotations
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from abc import ABC, abstractmethod
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from dataclasses import dataclass
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from aborist.document import Document
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@dataclass
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class DistillationResult:
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"""What a Distiller returns for one source.
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contributing_chunk_indices: 0-based indices into source_chunks that fed
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the core's content. The runner Merkle-proves each one against the
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source's document_root and stores those proofs in derivations.proof_blob.
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"""
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core: Document
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contributing_chunk_indices: list[int]
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class Distiller(ABC):
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"""Pure function: surface Document + its chunks -> core DistillationResult.
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Distillers must be deterministic — same source bytes produce the same core
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bytes. Bumping a distiller's algorithm requires bumping its `name`.
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"""
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name: str
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@abstractmethod
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def distill(
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self, source: Document, source_chunks: list[str]
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) -> DistillationResult:
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...
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