A campaign could already be exported and imported. What could not survive the trip was everything that explains it: the state events behind the authoritative document, the prompt each turn was actually given, the passages it was shown, the summaries that carry long-story continuity, and which take belonged to which turn. An imported campaign could be read and could no longer say why it was what it was — and a manual correction, the one state change no narration explains, was indistinguishable from something the story had established. The bundle is now `ai-dnd-adventure-v3`, and the version is the design rather than a side effect. Everything added here could have been another optional key, the way persona, Save Points, narrative state and imported knowledge each were. That mechanism stops working at exactly this addition: a v2 file with no prompt provenance is ambiguous between "written before M9" and "written by M9 from a campaign that has none", and those are different facts about a campaign. A version number is how a recovery file states what it was capable of recording. v1 and v2 still import, and every seam from pre-active-head onward is tested for the rule that an older file is never reinterpreted under a newer assumption. Two categories became three. "Chosen travels, derived is recomputed" was enough until stored prompts had to be decided: they are derived, and they must travel anyway. The test that separates evidence from cache is not "could this be recomputed" but "would a recomputation answer the same question" — a rebuilt search index answers the same question, a rebuilt prompt says what the turn would be told *now*, which is the opposite of what the inspector is for. Also here: a real SQLite backup, through the online backup API rather than a file copy, taken while the application is running and verified before it is kept; story cards settled as compatibility-only legacy data and taken out of the narrator's prompt, because they were the untracked path around knowledge authority that IMPORTED-KNOWLEDGE-DESIGN §73 already forbade; and no schema change at all, proved against a database M8's own code wrote. Three defects, found by running the milestone's own tests rather than by reading them. Deleting a campaign leaked its FTS index rows, and SQLite then handed the freed ids to the next source imported into any campaign, which failed with an integrity error that Reindex could not repair — both ends are closed, and a database already carrying the damage now repairs itself. An imported node with no state snapshot was being stamped with the campaign's head state, so an Undo to turn 2 showed what the story knew at turn 20. And the snapshot relink did not persist at all, because it mutated a dict in place on a column SQLAlchemy tracks by assignment: it looked correct in memory and wrote the wrong ids to disk. Carrying per-turn prompts looked like it would halve the length of campaign that can be restored. Measured — and after compressing them inside the file — everything M9 added costs 12% of it: the import ceiling moves from about 318 turns to about 279, against a 100-turn certification target. The dominant cost is not M9's at all. The per-position narrative state document is 74% of a bundle, and v2 already carried it. Backend 1,102 passed / 14 skipped / 0 failed. Frontend 145 passed. Lint, production build and Docker build clean. Verified across two server processes with two data directories, and in a real browser against a real narrator. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Qyn3oRd4D6pi72nKBG725B
265 lines
11 KiB
Python
265 lines
11 KiB
Python
"""How a campaign bundle grows with the campaign, measured rather than reasoned.
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python -m tools.m9_scale_report [--turns 120] [--budget 16384]
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Run from `backend/`. Plays a campaign of `--turns` turns against a scripted
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narrator with the real prompt builder and a realistic context budget, then
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exports it and reports where the bytes are.
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The question it exists to answer is the one M9's decision to carry historical
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prompts raises: **a per-turn prompt contains the story so far, so storing one per
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turn is quadratic in campaign length.** That is already true of the database —
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`compression.py` records the column as 89% of production storage — and M9 makes
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it true of the export as well. Reasoning about it gives the wrong number, because
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the prompt is bounded by the context budget rather than by the transcript: once
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the history window is full, each turn's snapshot stops growing and the total
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becomes linear again. Where that knee falls is a measurement.
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It also watches for the accidental costs §26 names: a query per row, a
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duplicated body of knowledge content, or a snapshot written more than once per
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turn.
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"""
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from __future__ import annotations
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import argparse
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import json
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import os
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import sys
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import tempfile
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import time
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from pathlib import Path
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_HERE = Path(__file__).resolve().parent
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sys.path.insert(0, str(_HERE.parent / "tests"))
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_DB = tempfile.NamedTemporaryFile(suffix="-m9-scale.db", delete=False)
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_DB.close()
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os.environ["AIDND_DB_PATH"] = _DB.name
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os.environ.pop("AIDND_DATABASE_URL", None)
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os.environ.pop("DATABASE_URL", None)
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from fastapi import Depends # noqa: E402
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from fastapi.testclient import TestClient # noqa: E402
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import m9_fixture # noqa: E402
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from app import auth, limits, memorybank, models # noqa: E402
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from app.database import Base, SessionLocal, engine, get_db # noqa: E402
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from app.main import app # noqa: E402
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from app.routers import adventures # noqa: E402
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from fakes import ScriptedProvider, state_block # noqa: E402
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#: Prose long enough that a turn is a turn rather than a sentence. The history
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#: window is what fills the prompt, so a fixture of three-word replies would
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#: measure a campaign nobody plays.
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PROSE = (
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"The rain came harder off the fen and the lantern light shivered on the wet "
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"boards. Mara set down the cloth she had been folding and looked at him for "
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"a while without saying anything, the way she did when the answer was going "
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"to cost her something. Outside, somebody crossed the yard and did not stop."
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)
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class _Stub:
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async def complete(self, system, prompt, **kwargs):
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return "The story had established a good deal by this point."
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async def embed(self, texts):
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return [[1.0, 0.5, 0.25, 0.125] for _ in texts]
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def _setup(budget: int) -> tuple[TestClient, int]:
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adventures.turns.OpenAICompatibleProvider = ScriptedProvider
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memorybank.embedding_provider = lambda s: _Stub()
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memorybank.summary_provider = lambda s: _Stub()
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limits.check_row_cap = lambda *a, **k: None
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Base.metadata.create_all(bind=engine)
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db = SessionLocal()
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try:
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user = models.User(is_guest=False, email="scale@example.com")
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db.add(user)
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db.flush()
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db.add(models.Settings(
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user_id=user.id, model="scale-model", embedding_model="stub",
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context_token_budget=budget, max_output_tokens=800,
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))
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adventure = models.Adventure(
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user_id=user.id, title="Scale", auto_summarize=True,
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memory_bank_enabled=True,
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campaign_canon=m9_fixture.CAMPAIGN_CANON,
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)
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db.add(adventure)
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db.flush()
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db.add(models.Action(
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adventure_id=adventure.id, type="start", text=m9_fixture.OPENING,
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))
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db.commit()
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adv_id, user_id = adventure.id, user.id
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finally:
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db.close()
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app.dependency_overrides[auth.get_current_user] = (
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lambda db=Depends(get_db): db.get(models.User, user_id)
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)
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return TestClient(app), adv_id
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def _bundle_bytes(client, adv_id) -> tuple[int, dict, float]:
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started = time.perf_counter()
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response = client.get(f"/api/adventures/{adv_id}/export")
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seconds = time.perf_counter() - started
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response.raise_for_status()
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payload = response.json()
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return len(json.dumps(payload).encode("utf-8")), payload, seconds
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def _snapshot_bytes(payload: dict) -> int:
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"""What the stored prompts cost **in the file**, which is the encoded size.
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Measured as they appear rather than decoded first: the question this report
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answers is how large the file gets and how close it comes to the import
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ceiling, so what counts is the bytes that actually travel.
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"""
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return sum(
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len(json.dumps(action[key]).encode("utf-8"))
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for action in payload["actions"]
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for key in ("contextSnapshotZ", "contextSnapshot")
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if action.get(key)
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)
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def _decoded_snapshot_bytes(payload: dict) -> int:
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"""What the same prompts would cost uncompressed, for the ratio."""
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from app import bundle as bundle_module
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total = 0
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for action in payload["actions"]:
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snapshot = (
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action.get("contextSnapshot")
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if isinstance(action.get("contextSnapshot"), dict)
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else bundle_module._unpacked(action.get("contextSnapshotZ"))
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)
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if isinstance(snapshot, dict):
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total += len(json.dumps(snapshot).encode("utf-8"))
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return total
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def _section_bytes(payload: dict) -> dict:
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"""What each v3 addition costs in the file, separately.
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Needed because "the snapshots are 21% of the file" does not answer "what did
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M9 add": the state events, the proposals and the summaries are v3 additions
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too, and a claim about M9's cost that counted only the prompts would be
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understating it.
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"""
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def size(value) -> int:
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return len(json.dumps(value).encode("utf-8"))
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per_node = {"contextSnapshotZ": 0, "id": 0, "parentId": 0}
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for action in payload["actions"]:
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for key in per_node:
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if key in action:
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per_node[key] += size(action[key]) + len(key) + 4
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return {
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"prompts (contextSnapshotZ)": per_node["contextSnapshotZ"],
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"state events": size(payload.get("stateEvents") or []),
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"state proposals": size(payload.get("stateProposals") or []),
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"summaries": size(payload.get("summaries") or []),
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"node ids + parentage": per_node["id"] + per_node["parentId"],
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"per-position state (v2 already)": sum(
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size(a["narrativeStateAfter"]) for a in payload["actions"]
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if "narrativeStateAfter" in a
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),
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}
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def main() -> int:
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument("--turns", type=int, default=120)
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parser.add_argument("--budget", type=int, default=16384)
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parser.add_argument("--every", type=int, default=20,
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help="report the running size every N turns")
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args = parser.parse_args()
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client, adv_id = _setup(args.budget)
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for name, body, kind in (
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("canon.md", m9_fixture.CANON_MD, "canon"),
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("reference.md", m9_fixture.REFERENCE_MD, "reference"),
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("secret.md", m9_fixture.SECRET_MD, "canon"),
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):
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m9_fixture.upload(client, adv_id, name, body, kind)
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print(f"budget {args.budget} tokens, {args.turns} turns\n")
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print(f"{'turns':>6} {'actions':>8} {'bundle B':>12} {'snapshots B':>13} "
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f"{'B/turn':>9} {'export s':>9} {'import s':>9}")
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rows = []
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sections: dict[int, dict] = {}
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for turn in range(1, args.turns + 1):
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ScriptedProvider.replies = [
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f"{PROSE} [{turn}]\n"
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+ state_block([{"type": "add_fact", "predicate": "tally",
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"value": turn * 10, "fact_id": f"tally-{turn}"}])
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]
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response = client.post(f"/api/adventures/{adv_id}/actions",
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json={"type": "do", "text": f"press on, {turn}"})
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assert response.status_code == 200, response.text[:300]
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if turn % args.every and turn != args.turns:
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continue
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m9_fixture.settle_derived(adv_id)
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size, payload, export_seconds = _bundle_bytes(client, adv_id)
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started = time.perf_counter()
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imported = client.post("/api/adventures/import", json=payload)
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import_seconds = time.perf_counter() - started
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assert imported.status_code == 201, imported.text[:300]
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client.delete(f"/api/adventures/{imported.json()['id']}")
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snapshots = _snapshot_bytes(payload)
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plain = _decoded_snapshot_bytes(payload)
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rows.append((turn, size, snapshots, plain))
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sections[turn] = _section_bytes(payload)
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print(f"{turn:>6} {len(payload['actions']):>8} {size:>12,} "
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f"{snapshots:>13,} {snapshots // turn:>9,} "
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f"{export_seconds:>9.3f} {import_seconds:>9.3f}")
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db_bytes = Path(_DB.name).stat().st_size
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last_turn, last_size, last_snapshots, last_plain = rows[-1]
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per_turn = last_snapshots // last_turn
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cap = limits.MAX_IMPORT_BODY_BYTES
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print()
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print(f"database on disk: {db_bytes:,} bytes")
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print(f"snapshot share of file: {100 * last_snapshots // last_size}%")
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print(f"stored uncompressed: {last_plain:,} bytes "
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f"({last_plain / max(last_snapshots, 1):.1f}x the encoded size)")
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print(f"import body cap: {cap:,} bytes")
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print(f"turns before the cap: ~{cap // max(per_turn, 1):,} "
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f"at the marginal rate above")
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# Growth between the last two samples says whether the per-turn cost has
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# settled. It should: once the history window fills the budget, a prompt
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# stops growing with the transcript and the total becomes linear.
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if len(rows) >= 2:
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(t0, _, s0, _p0), (t1, _, s1, _p1) = rows[-2], rows[-1]
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print(f"marginal cost, last {t1 - t0} turns: "
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f"{(s1 - s0) // max(t1 - t0, 1):,} bytes/turn")
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print()
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print("where the bytes are, at the last sample:")
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last = sections[last_turn]
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added = sum(v for k, v in last.items() if not k.endswith("(v2 already)"))
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for name, value in sorted(last.items(), key=lambda kv: -kv[1]):
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print(f" {name:34} {value:>12,} {100 * value / last_size:5.1f}%")
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print(f" {'--- everything v3 added':34} {added:>12,} "
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f"{100 * added / last_size:5.1f}%")
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without = last_size - added
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print(f" a v2 file of the same campaign {without:>12,}")
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print(f" ceiling with v3 additions: ~{int((cap / (last_size / last_turn**2)) ** 0.5):,} turns")
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print(f" ceiling without them: ~{int((cap / (without / last_turn**2)) ** 0.5):,} turns")
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app.dependency_overrides.clear()
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return 0
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if __name__ == "__main__":
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try:
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raise SystemExit(main())
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finally:
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try:
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os.unlink(_DB.name)
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except OSError:
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pass
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