Resilient LLM runner: model fallback chain, provider-death blacklist, cooldown, ANSI-repair

- llm.py: single retry/fallback/cooldown authority used by analyze/verify/pipeline
- provider [404] blacklists model + switches; rate limit escalates then cooldown
- unparsable model output (bad JSON/ANSI noise) skips to next model
- verify.py: DS_VERIFY_TIMEOUT, true rate-limit handling, honest FAILED reporting
- pipeline_all.py: honors model, reports verify status accurately
- aggregate.py: skip epNNNN_corrected.json strays (was duplicating ep 304)
- gitignore data outputs; drop stray analysis/analyst/analysts dirs
This commit is contained in:
n3wk
2026-08-29 03:26:56 +02:00
parent 06724d7dc1
commit 2719e4319d
6 changed files with 463 additions and 226 deletions
+49 -63
View File
@@ -5,6 +5,8 @@ Spots "strange assumptions" like attributing a 2023 cohost seat to Maddox.
Usage:
python verify.py # verify ALL existing analyses
python verify.py 361 373 # verify specific episodes
Retries, model fallback and provider cooldown live in llm.py (shared).
"""
import json
import os
@@ -18,12 +20,14 @@ try:
except Exception:
pass
from llm import run as llm_run
from llm import RateLimitError, ProviderError
from llm import VERIFY_TIMEOUT
from config import BASE_DIR
from feed import load_episodes
from download import slug as ep_slug
from facts import DOSSIER_PATH, CAST_SHEET
from analyze import (ANALYSIS_DIR, OPENCODE, run_opencode, strip_to_json,
validate)
from analyze import (ANALYSIS_DIR, OPENCODE, strip_to_json, validate)
from export_txt import txt_path
VERIFY_PROMPT = """You are the fact-checking archivist for The Dick Show project. Three files are attached:
@@ -77,72 +81,54 @@ def verify_episode(ep: dict, force: bool = False) -> dict | None:
return None
prompt = build_verify_prompt()
from analyze import RateLimitError
waits = [30, 120, 300, 600]
attempt = 0
last_err = None
while attempt < len(waits):
attempt += 1
try:
raw = run_opencode_multi(prompt, [attach_txt, DOSSIER_PATH, apath])
verdict = strip_to_json(raw)
v = verdict.get("verdict")
if v not in ("pass", "fix"):
raise ValueError(f"bad verdict: {v!r}")
if v == "pass":
current.setdefault("_verification", {
"verdict": "pass", "checked_at": _now(), "issues": []})
_save(apath, current)
print(f" verified OK (no issues)", flush=True)
return current
fixed = verdict.get("corrected_analysis")
def parse_verdict(raw: str) -> dict:
v = strip_to_json(raw)
verdict = v.get("verdict")
if verdict not in ("pass", "fix"):
raise ValueError(f"bad verdict: {verdict!r}")
if verdict == "fix":
fixed = v.get("corrected_analysis")
if not isinstance(fixed, dict):
raise ValueError("verdict=fix but no corrected_analysis")
validate(fixed)
issues = verdict.get("issues", [])
fixed["_verification"] = {"verdict": "fix", "checked_at": _now(),
"issues": issues}
fixed["ep_num"] = ep["ep_num"] if ep["ep_num"] else fixed.get("ep_num")
_save(apath, fixed)
print(f" FIXED {len(issues)} issue(s):", flush=True)
for i in issues[:6]:
print(f" - [{i.get('field')}] {str(i.get('issue'))[:90]}",
flush=True)
return fixed
except RateLimitError as e:
last_err = e
wait = waits[min(attempt, len(waits) - 1)]
print(f" verify rate-limited (attempt {attempt}); "
f"sleeping {wait}s ...", flush=True)
time.sleep(wait)
except Exception as e: # noqa: BLE001
last_err = e
wait = waits[min(attempt - 1, len(waits) - 1)]
print(f" verify attempt {attempt} failed: {e}; "
f"retry in {wait}s", flush=True)
time.sleep(wait)
print(f" verification FAILED for {ep['title']}: {last_err}", flush=True)
return None
return v
from datetime import datetime, timezone as _tz
try:
verdict = llm_run(prompt, [attach_txt, DOSSIER_PATH, apath],
timeout=VERIFY_TIMEOUT, label="verify",
parse=parse_verdict)
except (RateLimitError, ProviderError) as e:
print(f" verification NOT RUN for {ep['title']}: {e}", flush=True)
return None
v = verdict.get("verdict")
if v == "pass":
current.setdefault("_verification", {
"verdict": "pass",
"checked_at": datetime.now(_tz.utc).isoformat(), "issues": []})
_save(apath, current)
print(f" verified OK (no issues)", flush=True)
return current
fixed = verdict["corrected_analysis"]
issues = verdict.get("issues", [])
fixed["_verification"] = {"verdict": "fix",
"checked_at": datetime.now(_tz.utc).isoformat(),
"issues": issues}
fixed["ep_num"] = ep["ep_num"] if ep["ep_num"] else fixed.get("ep_num")
_save(apath, fixed)
print(f" FIXED {len(issues)} issue(s):", flush=True)
for i in issues[:6]:
print(f" - [{i.get('field')}] {str(i.get('issue'))[:90]}",
flush=True)
return fixed
def run_opencode_multi(prompt: str, attachments: list[str]) -> str:
from analyze import OPENCODE_MODEL
cmd = [OPENCODE, "run", "--auto"]
for a in attachments:
cmd += ["-f", a]
cmd += ["--dir", BASE_DIR]
if OPENCODE_MODEL:
cmd += ["-m", OPENCODE_MODEL]
cmd.append(prompt)
import subprocess
proc = subprocess.run(cmd, capture_output=True, text=True,
encoding="utf-8", errors="replace",
cwd=BASE_DIR, timeout=900)
out = proc.stdout or ""
if not out.strip() and proc.stderr:
raise RuntimeError(f"opencode produced no stdout: "
f"{proc.stderr[-400:]}")
return out
# compat shim: raw output only, JSON parsed by the caller
return llm_run(prompt, attachments, timeout=VERIFY_TIMEOUT,
label="verify")
def _now() -> str:
@@ -174,4 +160,4 @@ def main() -> None:
if __name__ == "__main__":
main()
main()