test(agent): controlled fixture KB + one-command fast loop for tool-calling iterations
The phase-72 iteration loop cleared the database, git-cloned the homelab repo, re-imported 38-51 documents and re-embedded per run — many minutes per iteration against a different KB every time (owner directive 2026-09-04: stop importing the homelab repo on every test run). Replace it with: - tests/fixtures/agent_kb/: 8 hand-written markdown docs (sources 'deployments'/'homelab') whose specifics (rack7, 10.77.42.0/24, VLAN 130, rbm-8842, 17 2 * * *, obsidian-bor:2026.7.14, 18765, 18443, ...) no model can guess; read targets carry non-topical filenames so their questions do not lexically seed them (the read must actually happen) - tests/fixtures/test_kb.dump.sql: data-only snapshot (TRUNCATE + INSERTs incl. embeddings, self-contained git_sources rows, static KB overview) — verified by round-trip checksum at build time - scripts/load_test_kb.py: one-off rebuild (real pipeline + embeddings, ~2s) that also prints the per-question retrieval report (all 10 battery questions must be grounded) - scripts/restore_test_kb.py: sub-second one-transaction restore (no git clone, no re-embedding) - scripts/agent_realmodel_check.py: the gate gains --restore / --mode fixture (curated 10-question battery with one unambiguously correct tool behavior per question) / --turns N (12s micro-loop) / --concurrency / per-turn + total wall timing, and a second accuracy metric (contract accuracy: well-formed calls targeting resolvable entities) alongside the phase-72 locked executed ratio — the re-read of a seeded doc is a copy-invariant model behavior (5 variants, 0/15 flipped) that the dedupe refusal counts as a failure - TOOL_CALLING_TESTING.md: the human-readable methodology (fast loop, design rules, metrics, copy levers + tried-and-reverted table, current standing, open design question) Measured: restore 0.03s; micro-loop ~12s; full loop ~43-55s; concurrency 2/3 gives no gain (endpoint serializes).
This commit is contained in:
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"""Build the controlled tool-calling test KB and snapshot it (one-off).
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The fixture KB lives in ``tests/fixtures/agent_kb/`` — two source
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directories (``deployments``, ``homelab``) with eight hand-written
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markdown documents whose specifics (``rack7``, ``10.77.42.0/24``,
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VLAN 130, port 18443, ntfy topic ``reese-uptime-7``, machine ID
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``rbm-8842``, the ``17 2 * * *`` schedule, image
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``ghcr.io/reese/obsidian-bor:2026.7.14``, port 18765, …) are not
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guessable by any model. This script:
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1. resets the app tables (one TRUNCATE — the dump's table set),
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2. registers the two fixture directories as ``kind='local'``
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``git_sources`` rows (so the source registry — and therefore
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``ls``'s scope names — is self-contained and independent of the
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``BOR_GIT_SOURCES`` env var),
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3. imports the fixture documents through the real pipeline
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(``import_sources`` — real chunking + real ``embed``-model
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embeddings; this is the ONLY step that burns model calls, and only
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at build time),
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4. stores the static KB overview + the sources-version row,
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5. prints a **retrieval report** for every fixture-battery question
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(grounded or deflected, which documents would seed) — the battery
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must be all-grounded for the gate to exercise the tools,
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6. snapshots the resulting database state into
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``tests/fixtures/test_kb.dump.sql`` — a data-only SQL script
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(TRUNCATE + one multi-row ``INSERT`` per app table, generated
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in-process — the same file runs in psql or psycopg, in one
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transaction) — and **verifies the snapshot by restoring it and
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comparing a per-table checksum**.
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Re-run it only when the fixture documents, the chunker, or the
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embedding model change — everyday iterations restore the dump in
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sub-second time (``scripts/restore_test_kb`` / the gate's
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``--restore``), never re-embedding (see ``TOOL_CALLING_TESTING.md``).
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Exit codes: **0** built + verified, **1** build/verification failure,
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**2** precondition failure.
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"""
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from __future__ import annotations
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import argparse
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import asyncio
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import json
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import logging
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import sys
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import time
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import uuid
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from datetime import datetime
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from pathlib import Path
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from dotenv import load_dotenv
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from sqlalchemy import select, text
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from sqlalchemy.orm import Session
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from app.api.chat import plan_turn
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from app.config import get_settings
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from app.db import SessionLocal, db_available
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from app.models import (
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Chunk,
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DocDraft,
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Document,
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GitSource,
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KbOverview,
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QueryLog,
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SavedChat,
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SourcesMeta,
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SteeringNote,
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)
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from app.rag.importer import import_sources
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from app.rag.llm import LLMClient
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from app.rag.retriever import retrieve
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logger = logging.getLogger("scripts.load_test_kb")
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DEFAULT_KB_DIR = Path("tests/fixtures/agent_kb")
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DEFAULT_DUMP = Path("tests/fixtures/test_kb.dump.sql")
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#: The two fixture source directories (source name = directory basename,
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#: the importer's rule). Alphabetical — the catalog order the derived
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#: battery reads.
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FIXTURE_SOURCES: tuple[str, ...] = ("deployments", "homelab")
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#: The KB overview stored with the fixture (id=1). A plain outline of
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#: the KB's basic categories — the ``<knowledge_base>`` prompt section
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#: of every turn. Static on purpose: the dump must be deterministic and
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#: the gate must not burn a ``lite`` call at restore time.
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FIXTURE_KB_OVERVIEW: str = (
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"deployments: the lab Ansible inventory (host addresses and roles), "
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"the Obsidian BOR quadlet service definition, and the GitLab Runner "
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"CI setup. homelab: the rack7 Proxmox cluster networking (bridges, "
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"VLANs, DNS/DHCP), container notes (Uptime Kuma, Qwen 3.8 on "
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"llama.cpp), and the nightly restic backup configuration."
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)
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#: (table, model, explicit column list — the generated ``chunks.tsv``
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#: tsvector column is excluded; Postgres recomputes it).
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_TABLES: tuple[tuple[str, type, tuple[str, ...]], ...] = (
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("documents", Document, ("id", "source", "path", "full_path", "title",
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"content", "content_hash", "indexed_at", "summary")),
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("chunks", Chunk, ("id", "document_id", "position", "content",
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"embedding", "is_summary")),
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("git_sources", GitSource, ("id", "url", "kind", "path", "added_at")),
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("kb_overview", KbOverview, ("id", "content", "updated_at")),
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("sources_meta", SourcesMeta, ("id", "version", "updated_at")),
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("steering_notes", SteeringNote, ("id", "note", "created_at")),
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("query_log", QueryLog, ("id", "question", "top_score", "fts_hits",
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"chunk_hits", "deflected", "sources",
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"latency_ms", "created_at")),
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("saved_chats", SavedChat, ("id", "title", "messages", "share_token",
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"sources_version", "created_at", "updated_at")),
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("doc_drafts", DocDraft, ("id", "token", "title", "path", "body",
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"status", "branch", "commit_sha", "created_at",
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"updated_at")),
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)
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# --------------------------------------------------------------------------
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# SQL serialization (the dump is plain multi-row INSERTs — the installed
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# psycopg build exposes no COPY API, and a multi-statement script with
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# inline ``COPY … FROM stdin`` data cannot be sent through any driver's
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# simple-protocol execute. INSERT VALUES is the portable form: the same
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# file runs in psql, psycopg, or anything else that speaks SQL, in one
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# transaction. With ``standard_conforming_strings`` on (the Postgres
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# default since 9.1), a string literal needs ONLY single-quote doubling —
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# backslashes are literal and newlines may be real.
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# --------------------------------------------------------------------------
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def _sql_value(value: object) -> str:
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"""One value as a SQL literal (``NULL`` for None)."""
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if value is None:
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return "NULL"
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if isinstance(value, bool):
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return "TRUE" if value else "FALSE"
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if isinstance(value, float):
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return repr(value) # shortest round-trip double
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if isinstance(value, int):
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return str(value)
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if isinstance(value, uuid.UUID):
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return "'" + str(value) + "'"
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if isinstance(value, datetime):
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return "'" + value.isoformat(sep=" ") + "'"
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if isinstance(value, (list, tuple)) and value and isinstance(value[0], float):
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# A pgvector vector: the ``[v1, v2, …]`` text literal (pgvector
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# 0.7+ format; the older ``{…}`` form is rejected). Checked
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# before the JSONB branch — a JSONB array of dicts never has a
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# float first element.
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return "'" + "[" + ",".join(repr(v) for v in value) + "]" + "'"
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if isinstance(value, (dict, list)):
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# JSONB columns: the stored JSON text (Postgres re-parses it).
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text_ = json.dumps(value, ensure_ascii=False, separators=(",", ":"))
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else:
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text_ = str(value)
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return "'" + text_.replace("'", "''") + "'"
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def _dump_table(db: Session, table: str, model: type, columns: tuple[str, ...]) -> str:
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"""One multi-row ``INSERT INTO <table> (…) VALUES (…), …;`` statement
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(an empty table emits nothing — there is no row to write)."""
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rows = db.execute(select(model)).all()
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value_rows = [
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"(" + ", ".join(_sql_value(getattr(row[0], name)) for name in columns) + ")"
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for row in rows
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]
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if not value_rows:
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return ""
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return (
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f"INSERT INTO public.{table} ({', '.join(columns)}) VALUES "
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+ ",\n".join(value_rows)
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+ ";\n"
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)
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def _table_checksum(db: Session, table: str) -> str:
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"""An order-independent content checksum for *table* (row::text,
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sorted aggregation) — the snapshot round-trip check."""
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return db.execute(
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text(
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"select md5(coalesce(string_agg(r, E'\\n' order by r), '')) "
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f"from (select t::text as r from public.{table} t) s"
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)
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).scalar_one()
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async def _retrieval_report(llm: LLMClient, battery: list[str]) -> int:
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"""Print, per battery question, what the real path would do:
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grounded or deflected, and which documents would seed the context.
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Returns the number of deflected questions (a loud warning — the
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gate needs tools offered on its turns)."""
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settings = get_settings()
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deflected = 0
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print("\nretrieval report (the honesty gate per battery question):")
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with SessionLocal() as db:
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for number, question in enumerate(battery, start=1):
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vec = await llm.embed_one(question)
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chunks = retrieve(db, question, vec)
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plan = plan_turn(chunks, settings)
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seed = ", ".join(f"{d.source}/{d.path}" for d in plan.docs) or "—"
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if plan.deflected:
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deflected += 1
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print(
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f" {number:02d}. {'DEFLECTED ' if plan.deflected else 'grounded '} "
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f"(best={plan.top_score:.3f} fts={plan.fts_hits}) "
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f"seed: {seed}\n ← {question}"
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)
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return deflected
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async def _build(kb_dir: Path, dump_path: Path) -> int:
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from scripts.agent_realmodel_check import FIXTURE_BATTERY
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started = time.monotonic()
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if not db_available():
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print(
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"load_test_kb: precondition failed — database unreachable; "
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"start Postgres with `podman compose up -d db`"
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)
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return 2
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source_dirs = [kb_dir / name for name in FIXTURE_SOURCES]
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missing = [str(p) for p in source_dirs if not p.is_dir()]
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if missing:
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print(f"load_test_kb: precondition failed — missing source dir(s): {missing}")
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return 2
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# 1. Reset the dump's table set (one statement — the inter-table FKs
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# resolve within it).
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table_list = ", ".join(f"public.{table}" for table, _m, _c in _TABLES)
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with SessionLocal() as db:
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db.execute(text(f"TRUNCATE {table_list}"))
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for directory in source_dirs:
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absolute = str(directory.resolve())
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db.add(GitSource(url=absolute, kind="local", path=absolute))
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db.commit()
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logger.info("load_test_kb: tables reset; %d local source rows added", len(source_dirs))
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# 2. Import through the real pipeline (the only model-cost step).
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llm = LLMClient()
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summary = await import_sources([p.resolve() for p in source_dirs], llm)
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if summary.errors:
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print(f"load_test_kb: {summary.errors} file(s) failed to import — aborting")
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return 1
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if summary.added == 0:
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print("load_test_kb: no documents imported — aborting")
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return 1
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logger.info(
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"load_test_kb: imported added=%d chunks=%d embed_batches=%d",
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summary.added, summary.chunks, summary.embed_batches,
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)
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# 3. The static overview + sources version.
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with SessionLocal() as db:
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overview = db.get(KbOverview, 1) or KbOverview(id=1)
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overview.content = FIXTURE_KB_OVERVIEW
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meta = db.get(SourcesMeta, 1) or SourcesMeta(id=1)
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meta.version = 1
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db.add(overview)
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db.add(meta)
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db.commit()
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# 4. Retrieval report (all battery questions must stay grounded).
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n_deflected = await _retrieval_report(llm, list(FIXTURE_BATTERY))
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if n_deflected:
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print(
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f"\nload_test_kb: WARNING — {n_deflected} battery question(s) would "
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"DEFLECT in the real path (no tools offered). Adjust the fixture "
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"content (a lexical anchor for the question's words) or the "
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"question before running the gate."
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)
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# 5. Snapshot (data-only) + round-trip verification.
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with SessionLocal() as db:
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before = {table: _table_checksum(db, table) for table, _m, _c in _TABLES}
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parts = [
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"-- ============================================================",
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"-- Brain of Reese — controlled tool-calling test KB (fixture dump)",
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f"-- Generated by scripts/load_test_kb.py on "
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f"{datetime.now().astimezone().isoformat(timespec='seconds')}",
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"-- Data-only snapshot (the schema stays alembic-managed; the",
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"-- generated chunks.tsv column is recomputed on restore).",
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f"-- Sources: {', '.join(FIXTURE_SOURCES)} "
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f"({summary.added} documents, {summary.chunks} chunks).",
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"-- Restore (one transaction, sub-second):",
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"-- uv run python -m scripts.restore_test_kb",
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"-- psql \"$BOR_DATABASE_URL\" --single-transaction -f "
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"tests/fixtures/test_kb.dump.sql",
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"-- ============================================================",
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f"TRUNCATE {table_list};",
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"",
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]
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for table, model, columns in _TABLES:
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parts.append(_dump_table(db, table, model, columns))
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script = "\n".join(parts)
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dump_path.parent.mkdir(parents=True, exist_ok=True)
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dump_path.write_text(script, encoding="utf-8")
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logger.info("load_test_kb: dump written: %s (%d KB)", dump_path, len(script) // 1024)
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# Round-trip: restore the dump over the (identical) state and compare
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# the per-table checksums — a serialization bug must fail the build.
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from scripts.restore_test_kb import restore_dump
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restore_dump(dump_path) # RuntimeError on failure → the build fails
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with SessionLocal() as db:
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after = {table: _table_checksum(db, table) for table, _m, _c in _TABLES}
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mismatched = [t for t, c in before.items() if after.get(t) != c]
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if mismatched:
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print(f"load_test_kb: VERIFICATION FAILED — checksum mismatch: {mismatched}")
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return 1
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wall = time.monotonic() - started
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print(
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f"load_test_kb: ok — docs={summary.added} chunks={summary.chunks} "
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f"sources={len(FIXTURE_SOURCES)} dump={dump_path} "
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f"({dump_path.stat().st_size // 1024} KB, verified by round-trip) "
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f"in {wall:.1f}s"
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)
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return 0
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def main(argv: list[str] | None = None) -> int:
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# CLI-only: pick up .env without side effects on import (the house
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# probe pattern, cf. scripts/llm_probe.py).
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load_dotenv()
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parser = argparse.ArgumentParser(
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description=(
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"Build the controlled tool-calling test KB from "
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"tests/fixtures/agent_kb (real embeddings, once) and snapshot "
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"it to tests/fixtures/test_kb.dump.sql (verified by "
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"round-trip). Exit 0 built+verified, 1 failure, 2 precondition."
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)
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)
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parser.add_argument(
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"--kb-dir", type=Path, default=DEFAULT_KB_DIR,
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help=f"the fixture KB root (default: {DEFAULT_KB_DIR})",
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)
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parser.add_argument(
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"--dump", type=Path, default=DEFAULT_DUMP,
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help=f"the dump file to write (default: {DEFAULT_DUMP})",
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)
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args = parser.parse_args(argv)
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logging.basicConfig(
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level=logging.INFO, format="%(levelname)s %(name)s: %(message)s"
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)
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return asyncio.run(_build(args.kb_dir, args.dump))
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if __name__ == "__main__":
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sys.exit(main())
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Reference in New Issue
Block a user