tools: distinguish "captured in time" from "still alive"
analyze_media_age.py claimed age was ruled out because an image from
2025-11 was saved while one from 2026-08 was not. That conclusion does not
follow. "Saved" means some earlier run downloaded it, not that ChatGPT
still holds it — an image captured in June looks saved forever after, even
if it died in July. A month with no losses shows the exports were timely,
not that the assets survived.
- probe_survival_by_month.py: sample images already on disk, grouped by
their conversation's month, and ask /files/{id} whether each still
exists today. Old months still 200 → no expiry, and cadence did not save
them. Old months now 404 → uploads do expire and cadence is the whole
ballgame.
- analyze_media_age.py: stop asserting the unsupported verdict; say what
the number does and does not show, and point at the probe.
One signal there is immune to the confound and survives: 2026-07-09 kept
38 images and lost 12. Same conversation, same day, opposite outcomes —
no retention policy does that, so at least part of this is per-asset.
This commit is contained in:
JesseMarkowitz
@@ -20,6 +20,15 @@ grouping outcomes by month and by source distinguishes the hypotheses:
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* Neither → deaths scattered across months, or concentrated in a
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few conversations while their neighbours survive.
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IMPORTANT — what "saved" does and does not mean. It means the image was
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downloaded by *some* run at *some* point, not that ChatGPT still holds it. An
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image captured in June looks saved forever after, even if it died in July. So
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a month with no losses shows the exports were timely; it cannot show the
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assets survived. Use probe_survival_by_month.py to ask the API what is still
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live today. The one signal here that is immune to this confound is a single
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conversation that both kept and lost images: same age, same chat, opposite
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outcomes means the cause is per-asset, not retention.
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Run from the project root:
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python tools/analyze_media_age.py
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@@ -123,12 +132,21 @@ def main() -> None:
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print(f" dead range : {old_d or '—'} … {new_d or '—'}")
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if old_s and new_d and old_s < new_d:
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print(
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f" → an asset from {old_s} survived while one from "
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f"{new_d} did not: age alone does not explain the loss."
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f" → an asset from {old_s} was captured while one from "
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f"{new_d} was not."
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)
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print(
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" This does NOT disprove expiry: 'captured' means some "
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"run got it in time,"
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)
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print(
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" not that it is still on ChatGPT today. Run "
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"probe_survival_by_month.py to tell"
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)
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print(" those apart.")
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elif old_s and old_d and old_s > old_d:
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print(
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f" → everything dead is older than everything alive "
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f" → everything lost is older than everything captured "
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f"(cutoff between {old_d} and {old_s}): consistent with expiry."
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)
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print()
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@@ -0,0 +1,153 @@
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"""Are already-downloaded images still alive on ChatGPT, or did we just catch them in time?
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analyze_media_age.py cannot answer this. It reports whether an image was ever
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captured — and an image downloaded by a run back in June looks "saved" forever
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after, whether or not ChatGPT still holds it today. So a month with zero losses
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proves the exports were timely, not that the assets survived.
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This closes that gap: take images that ARE on disk, grouped by the month of
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their conversation, and ask the API whether each still exists right now.
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Old months still 200 → assets do not expire with age. Export cadence is not
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what saved them, and shortening it would not have
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saved the July losses either.
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Old months now 404 → assets DO die with age; the old months are on disk
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only because a run reached them in time. Cadence is
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the whole ballgame, and the July losses are the first
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ones we simply arrived too late for.
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Liveness is checked with /files/{id}, which answers a missing record with a
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clean 404 (verified 2026-08-17); /files/{id}/download reports the same state
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as a misleading 403.
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Run from the project root:
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python tools/probe_survival_by_month.py [samples_per_month]
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"""
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import os
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import re
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import sys
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from collections import defaultdict
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
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from dotenv import load_dotenv
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load_dotenv()
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from src.providers.chatgpt import BASE_URL, ChatGPTProvider # noqa: E402
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SAVED_RE = re.compile(r"!\[([^\]]*)\]\((media/[^)]+)\)")
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DATE_RE = re.compile(r"(\d{4}-\d{2}-\d{2})_")
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DEFAULT_SAMPLES = 4
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def collect_saved_ids(export_dir: Path) -> dict[str, list[tuple[str, str]]]:
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"""month → [(file_id, source)] for images already downloaded to disk."""
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by_month: dict[str, list[tuple[str, str]]] = defaultdict(list)
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for md in export_dir.rglob("*.md"):
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date_match = DATE_RE.search(md.name)
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if not date_match:
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continue
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month = date_match.group(1)[:7]
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try:
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text = md.read_text(encoding="utf-8", errors="replace")
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except OSError:
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continue
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for source, rel_path in SAVED_RE.findall(text):
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file_id = Path(rel_path).stem
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if file_id.startswith("file"):
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by_month[month].append((file_id, source or "unknown"))
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return by_month
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def main() -> None:
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samples = DEFAULT_SAMPLES
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if len(sys.argv) > 1:
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try:
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samples = max(1, int(sys.argv[1]))
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except ValueError:
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pass
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export_dir = Path(os.getenv("EXPORT_DIR", "./exports")).expanduser()
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by_month = collect_saved_ids(export_dir)
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if not by_month:
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print(f"no downloaded images found under {export_dir}")
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return
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provider = ChatGPTProvider()
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print("=" * 78)
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print(f"Are on-disk images still live on ChatGPT? ({samples} sampled per month)")
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print("=" * 78)
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print(f"{'month':<9} {'alive':>6} {'gone':>6} {'err':>5} sampled sources")
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totals = {"alive": 0, "gone": 0, "err": 0}
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verdict_rows: list[tuple[str, int, int]] = []
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for month in sorted(by_month):
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entries = by_month[month]
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# Spread the sample across the month rather than taking the first few
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# from one conversation.
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step = max(1, len(entries) // samples)
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picked = entries[::step][:samples]
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alive = gone = err = 0
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sources: list[str] = []
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for file_id, source in picked:
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sources.append(source[:4])
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try:
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provider._pace()
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resp = provider._session.request(
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"GET", f"{BASE_URL}/files/{file_id}", timeout=30
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)
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except Exception: # noqa: BLE001 - diagnostic
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err += 1
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continue
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if resp.status_code == 200:
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alive += 1
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elif resp.status_code == 404:
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gone += 1
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else:
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err += 1
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totals["alive"] += alive
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totals["gone"] += gone
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totals["err"] += err
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verdict_rows.append((month, alive, gone))
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print(
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f"{month:<9} {alive:>6} {gone:>6} {err:>5} "
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f"{','.join(sources)} (of {len(entries)} on disk)"
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)
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print()
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print(f"total: {totals['alive']} alive, {totals['gone']} gone, {totals['err']} error")
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print()
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print("=" * 78)
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print("Verdict")
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print("=" * 78)
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old_gone = [m for m, _a, g in verdict_rows[:-2] if g]
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old_alive = [m for m, a, _g in verdict_rows[:-2] if a]
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if old_gone and not old_alive:
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print(" Every sampled older image is GONE from ChatGPT.")
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print(" → Uploads expire. Your old exports survive only because a run")
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print(" reached them in time. Export cadence directly determines")
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print(" what you can still save.")
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elif old_alive and not old_gone:
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print(" Every sampled older image is STILL LIVE on ChatGPT.")
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print(" → Uploads do not expire with age. The July losses are")
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print(" something else, and exporting sooner would not have")
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print(" prevented them.")
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else:
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print(" Mixed: some older images alive, some gone.")
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print(" → Not a clean expiry. Compare the 'sampled sources' column and")
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print(" the per-month rates above; the cause is likely per-asset.")
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if __name__ == "__main__":
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main()
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