feat: write leafs incrementally without rebuilding the graph.
Ladybug 0.19 stays FTS/HNSW queryable on MERGE of new ids; DROP INDEX was the fatal path. bin/brain/add.go and POST /ingest land facts+info in one transaction so watch/mail/git can become leafs now (Gitea #14).
This commit is contained in:
Executable
+21
@@ -0,0 +1,21 @@
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//usr/bin/env go run -tags=brain_add "$0" "$@"; exit
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//go:build brain_add
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//
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// bin/brain/add.go - incremental leaf write (Python kblib, no rebuild).
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//
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// ./bin/brain/add.go --text T --root facts --source "a.md x b.md"
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// ./bin/brain/add.go --json
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//
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// D6: write stays Python. Does not delete var/kb.lbug.
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// NOTE: never run `gofmt -w` on this file — it breaks the shebang.
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package main
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import (
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"os"
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"github.com/eSlider/2dph/internal/cmdbin"
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)
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func main() {
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os.Exit(cmdbin.ExecFile("bin/kb/add", os.Args[1:]))
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}
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+2
-2
@@ -7,8 +7,8 @@
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// ./bin/brain/index.go --rebuild --with-mail
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// ./bin/brain/index.go --dry-run --with-mail
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//
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// v1 write is always a rebuild when mail is included (live FTS/HNSW + bulk
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// insert corrupts Ladybug 0.19 WAL). `add` is v2.
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// v1 write: bin/brain/add.go for one/few leafs (indexes may already exist).
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// Bulk mail/corpus still --rebuild (fresh file, indexes last).
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// NOTE: never run `gofmt -w` on this file — it breaks the shebang.
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package main
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Executable
+114
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#!/usr/bin/env python3
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"""kb/add - incremental leaf write (no rebuild).
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bin/kb/add --text T --root facts|info --source S
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bin/kb/add --json # stdin: one object or {"leafs":[...]}
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bin/kb/add --db PATH --json
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Writes facts+info in one Ladybug transaction. Does not delete kb.lbug.
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Embedding is used when provided; otherwise model2vec encodes the text.
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"""
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from __future__ import annotations
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import json
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import sys
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[2]
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sys.path.insert(0, str(ROOT / "bin" / "tools"))
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from kblib import ( # noqa: E402
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EMBED_DIM,
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add_leafs,
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connect,
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ensure_indexes,
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init_schema,
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)
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def _as_leafs(payload: object) -> list[dict]:
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if isinstance(payload, list):
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return [dict(x) for x in payload]
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if isinstance(payload, dict):
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if "leafs" in payload:
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return [dict(x) for x in payload["leafs"]]
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return [dict(payload)]
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raise ValueError("json must be an object, a list, or {leafs:[...]}")
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def _embed_missing(leafs: list[dict]) -> None:
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missing = [lf for lf in leafs if not lf.get("embedding")]
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if not missing:
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return
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from model2vec import StaticModel
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model = StaticModel.from_pretrained("minishlab/potion-multilingual-128M")
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for lf in missing:
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text = str(lf.get("text") or "")
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vec = model.encode([text])[0].astype(float).tolist()
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if len(vec) != EMBED_DIM:
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vec = (vec + [0.0] * EMBED_DIM)[:EMBED_DIM]
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lf["embedding"] = vec
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def main(argv: list[str]) -> int:
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import argparse
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p = argparse.ArgumentParser(description="add leafs without rebuilding the brain")
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p.add_argument("--db", default="", help="path to kb.lbug (default var/kb.lbug)")
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p.add_argument("--json", action="store_true", help="read leaf JSON from stdin")
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p.add_argument("--text", default="", help="leaf text")
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p.add_argument("--root", default="info", choices=("facts", "info"))
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p.add_argument("--source", default="")
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p.add_argument("--confidence", default="confirmed")
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p.add_argument("--source-rev", default="working-tree")
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p.add_argument("--how", default="brain/add")
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p.add_argument("--loc", default="")
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p.add_argument("--type", default="reference", dest="type_")
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args = p.parse_args(argv)
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if args.json:
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raw = sys.stdin.read()
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if not raw.strip():
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print("kb/add: empty stdin", file=sys.stderr)
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return 2
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leafs = _as_leafs(json.loads(raw))
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else:
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if not args.text or not args.source:
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print("kb/add: --text and --source are required (or --json)", file=sys.stderr)
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return 2
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leafs = [{
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"text": args.text,
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"root": args.root,
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"source": args.source,
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"confidence": args.confidence,
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"source_rev": args.source_rev,
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"how": args.how,
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"loc": args.loc or args.source,
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"type": args.type_,
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}]
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for lf in leafs:
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if not lf.get("text") or not lf.get("source"):
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print("kb/add: each leaf needs text and source", file=sys.stderr)
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return 2
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_embed_missing(leafs)
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from kblib import DB_PATH, VAR
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dbpath = Path(args.db) if args.db else DB_PATH
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dbpath.parent.mkdir(parents=True, exist_ok=True)
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VAR.mkdir(exist_ok=True)
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db, conn = connect(dbpath, read_only=False)
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init_schema(conn)
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ids = add_leafs(conn, leafs)
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ensure_indexes(conn)
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conn.close()
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db.close()
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print(json.dumps({"mode": "add", "ids": ids, "db": str(dbpath)}))
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return 0
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if __name__ == "__main__":
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sys.exit(main(sys.argv[1:]))
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+45
-1
@@ -4,7 +4,7 @@ Single embedded graph `var/kb.lbug`. Two roots: facts (assertions backed by
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>=2 independent sources) and info (narrative leafs). Hybrid retrieval: BM25
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(FTS extension) + HNSW cosine (VECTOR extension) + Cypher graph hops.
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All access is read-only unless `--rebuild` is passed to kb/index.
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All access is read-only unless `--rebuild` (kb/index) or `kb/add`.
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"""
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from __future__ import annotations
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@@ -118,6 +118,50 @@ def upsert_leaf(conn: ladybug.Connection, *, text: str, root: str, confidence: s
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return lid
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def add_leafs(conn: ladybug.Connection, leafs: list[dict]) -> list[str]:
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"""Write facts+info leafs in one transaction. Safe while FTS/HNSW exist.
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Each leaf dict: text, source, optional root/confidence/source_rev/how/loc/type/embedding.
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Does not delete the database file. Measured on Ladybug 0.19: MERGE of new
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ids (and updates) stays FTS+HNSW queryable; DROP INDEX is the fatal path.
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"""
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if not leafs:
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return []
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started = False
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try:
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conn.execute("BEGIN TRANSACTION")
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started = True
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except Exception:
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started = False
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ids: list[str] = []
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try:
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for lf in leafs:
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ids.append(
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upsert_leaf(
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conn,
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text=str(lf["text"]),
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root=str(lf.get("root") or ROOT_INFO),
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confidence=str(lf.get("confidence") or CONF_CONFIRMED),
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source=str(lf["source"]),
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source_rev=str(lf.get("source_rev") or "working-tree"),
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how=str(lf.get("how") or "brain/add"),
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loc=str(lf.get("loc") or lf.get("source") or ""),
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type_=str(lf.get("type") or lf.get("type_") or "reference"),
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embedding=lf.get("embedding"),
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)
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)
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if started:
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conn.execute("COMMIT")
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except Exception:
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if started:
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try:
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conn.execute("ROLLBACK")
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except Exception:
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pass
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raise
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return ids
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def leaf_index_names(conn: ladybug.Connection) -> set[str]:
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"""Return index names on the Leaf table (e.g. {'id', 'Leaf_vec', '_PK'})."""
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rows = conn.execute("CALL SHOW_INDEXES() RETURN *").get_all()
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@@ -75,9 +75,20 @@ class BinLayoutTest(unittest.TestCase):
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)
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def test_brain_methods_are_shebangs(self) -> None:
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for method in ("index.go", "get.go", "stats.go", "eval.go", "watch.go"):
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for method in ("index.go", "add.go", "get.go", "stats.go", "eval.go", "watch.go"):
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self._assert_shebang(f"bin/brain/{method}")
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def test_brain_add_is_python_write_not_rebuild(self) -> None:
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self._assert_shebang("bin/brain/add.go")
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text = (ROOT / "bin" / "brain" / "add.go").read_text()
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self.assertIn("cmdbin.ExecFile", text)
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self.assertIn("bin/kb/add", text)
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self.assertNotIn("--rebuild", text)
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py = (ROOT / "bin" / "kb" / "add").read_text()
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self.assertIn("add_leafs", py)
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self.assertIn("--json", py)
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self.assertNotIn("unlink", py.lower())
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def test_brain_get_stats_eval_are_not_python_exec(self) -> None:
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for method in ("get.go", "stats.go", "eval.go"):
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text = (ROOT / "bin" / "brain" / method).read_text()
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@@ -0,0 +1,69 @@
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"""Incremental add writes leafs without deleting kb.lbug."""
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from __future__ import annotations
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import json
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import os
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import subprocess
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import sys
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import tempfile
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import unittest
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[2]
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class KbAddCLITest(unittest.TestCase):
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def test_json_add_does_not_delete_db(self) -> None:
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tmp = Path(tempfile.mkdtemp())
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dbpath = tmp / "kb.lbug"
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py = sys.executable
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venv_py = ROOT / ".venv" / "bin" / "python"
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if venv_py.is_file():
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py = str(venv_py)
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payload = {
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"text": "cli zebra leaf",
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"root": "info",
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"source": "cli-test",
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"confidence": "confirmed",
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"how": "test",
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"loc": str(tmp),
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"type": "reference",
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"embedding": [0.0] * 256,
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}
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payload["embedding"][0] = 0.3
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proc = subprocess.run(
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[py, str(ROOT / "bin" / "kb" / "add"), "--db", str(dbpath), "--json"],
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cwd=ROOT,
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input=json.dumps(payload),
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capture_output=True,
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text=True,
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env=os.environ.copy(),
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check=False,
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)
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self.assertEqual(proc.returncode, 0, proc.stderr)
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self.assertTrue(dbpath.exists(), "add must create the db, not skip write")
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out = json.loads(proc.stdout)
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self.assertEqual(out.get("mode"), "add")
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self.assertEqual(len(out.get("ids") or []), 1)
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again = subprocess.run(
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[py, str(ROOT / "bin" / "kb" / "add"), "--db", str(dbpath), "--json"],
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cwd=ROOT,
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input=json.dumps({
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**payload,
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"text": "second moose leaf",
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"source": "cli-test-2",
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}),
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capture_output=True,
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text=True,
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env=os.environ.copy(),
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check=False,
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)
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self.assertEqual(again.returncode, 0, again.stderr)
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self.assertTrue(dbpath.exists())
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second = json.loads(again.stdout)
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self.assertEqual(len(second.get("ids") or []), 1)
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self.assertNotEqual(out["ids"][0], second["ids"][0])
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if __name__ == "__main__":
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unittest.main()
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@@ -71,6 +71,69 @@ class KblibTest(unittest.TestCase):
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self.assertTrue(hits)
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self.assertIn("Leaf_vec", kblib.leaf_index_names(self.conn))
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def test_add_after_indexes_keeps_fts_queryable(self):
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"""Incremental add after FTS+HNSW must find the new leaf on both indexes."""
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kblib.upsert_leaf(self.conn, text="seed fox leaf", root="info",
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confidence="confirmed", source="s", source_rev="r1",
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how="test", loc="/tmp", type_="reference",
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embedding=make_emb(0.1))
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kblib.ensure_indexes(self.conn)
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ids = kblib.add_leafs(self.conn, [{
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"text": "added zebra after index",
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"root": "facts",
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"confidence": "confirmed",
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"source": "a.md x b.md",
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"source_rev": "r1",
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"how": "test",
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"loc": "/tmp",
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"type": "fact",
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"embedding": make_emb(0.9),
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}])
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self.assertEqual(len(ids), 1)
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fts = kblib.query_fts(self.conn, "zebra", 5)
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self.assertTrue(fts)
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self.assertIn("zebra", fts[0]["text"])
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self.assertEqual(fts[0]["root"], "facts")
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vec = kblib.query_vector(self.conn, make_emb(0.9), 5)
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self.assertTrue(any("zebra" in h["text"] for h in vec))
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fox = kblib.query_fts(self.conn, "fox", 5)
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self.assertTrue(fox)
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self.assertIn("fox", fox[0]["text"])
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def test_add_facts_and_info_one_transaction(self):
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"""D12: facts and info land in the same transaction."""
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kblib.ensure_indexes(self.conn)
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ids = kblib.add_leafs(self.conn, [
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{
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"text": "tx fact leaf two-source",
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"root": "facts",
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"confidence": "confirmed",
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"source": "compose.yml x docker ps",
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"source_rev": "r1",
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"how": "test",
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"loc": "/tmp",
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"type": "fact",
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"embedding": make_emb(0.4),
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},
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{
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"text": "tx info narrative",
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"root": "info",
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"confidence": "confirmed",
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"source": "note.md",
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"source_rev": "r1",
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"how": "test",
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"loc": "/tmp",
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"type": "reference",
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"embedding": make_emb(0.5),
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},
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])
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self.assertEqual(len(ids), 2)
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stats = kblib.stats(self.conn)
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self.assertEqual(stats["by_root"].get("facts"), 1)
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self.assertEqual(stats["by_root"].get("info"), 1)
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self.assertTrue(kblib.query_fts(self.conn, "two-source", 5))
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self.assertTrue(kblib.query_fts(self.conn, "narrative", 5))
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def test_drop_vector_then_create_raises_clear_error(self):
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"""DROP INDEX leaves ghost catalog; create_fts_and_vector must raise."""
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kblib.upsert_leaf(self.conn, text="seed", root="info",
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Reference in New Issue
Block a user