m3taversal
05d74d5e32
Imports 67 files from VPS (/opt/teleo-eval/) into repo as the single source of truth. Previously only 8 of 67 files existed in repo — the rest were deployed directly to VPS via SCP, causing massive drift. Includes: - pipeline/lib/: 33 Python modules (daemon core, extraction, evaluation, merge, cascade, cross-domain, costs, attribution, etc.) - pipeline/: main daemon (teleo-pipeline.py), reweave.py, batch-extract-50.sh - diagnostics/: 19 files (4-page dashboard, alerting, daily digest, review queue, tier1 metrics) - agent-state/: bootstrap, lib-state, cascade inbox processor, schema - systemd/: service unit files for reference - deploy.sh: rsync-based deploy with --dry-run, syntax checks, dirty-tree gate - research-session.sh: updated with Step 8.5 digest + cascade inbox processing No new code written — all files are exact copies from VPS as of 2026-04-06. From this point forward: edit in repo, commit, then deploy.sh. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
551 lines
20 KiB
Python
551 lines
20 KiB
Python
"""Post-extraction validator — deterministic fixes and quality gate.
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Runs AFTER LLM extraction, BEFORE git commit. Pure Python, $0 cost.
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Catches the mechanical issues that account for 73% of eval rejections:
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- Frontmatter schema violations (missing/invalid fields)
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- Broken wiki links (strips brackets, keeps text)
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- Date errors (wrong format, source date instead of today)
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- Filename convention violations
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- Title precision (too short, not a proposition)
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- Duplicate detection against existing KB
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Design principles (Leo):
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- Mechanical rules belong in code, not prompts
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- Fix what's fixable, reject what's not
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- Never silently drop content — log everything
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Epimetheus owns this module. Leo reviews changes.
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"""
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import json
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import logging
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import os
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import re
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from datetime import date, datetime
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from difflib import SequenceMatcher
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from pathlib import Path
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logger = logging.getLogger("pipeline.post_extract")
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# ─── Constants ──────────────────────────────────────────────────────────────
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VALID_DOMAINS = frozenset({
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"internet-finance", "entertainment", "health", "ai-alignment",
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"space-development", "grand-strategy", "mechanisms", "living-capital",
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"living-agents", "teleohumanity", "critical-systems",
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"collective-intelligence", "teleological-economics", "cultural-dynamics",
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})
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VALID_CONFIDENCE = frozenset({"proven", "likely", "experimental", "speculative"})
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REQUIRED_CLAIM_FIELDS = ("type", "domain", "description", "confidence", "source", "created")
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REQUIRED_ENTITY_FIELDS = ("type", "domain", "description")
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WIKI_LINK_RE = re.compile(r"\[\[([^\]]+)\]\]")
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# Minimum title word count for claims (Leo: titles must name specific mechanism)
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MIN_TITLE_WORDS = 8
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DEDUP_THRESHOLD = 0.85
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# ─── YAML parsing ──────────────────────────────────────────────────────────
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def parse_frontmatter(text: str) -> tuple[dict | None, str]:
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"""Extract YAML frontmatter from markdown. Returns (frontmatter_dict, body)."""
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if not text.startswith("---"):
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return None, text
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end = text.find("---", 3)
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if end == -1:
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return None, text
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raw = text[3:end]
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body = text[end + 3:].strip()
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try:
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import yaml
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fm = yaml.safe_load(raw)
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if not isinstance(fm, dict):
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return None, body
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return fm, body
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except ImportError:
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pass
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except Exception:
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return None, body
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# Fallback: simple key-value parser
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fm = {}
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for line in raw.strip().split("\n"):
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line = line.strip()
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if not line or line.startswith("#"):
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continue
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if ":" not in line:
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continue
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key, _, val = line.partition(":")
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key = key.strip()
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val = val.strip().strip('"').strip("'")
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if val.lower() == "null" or val == "":
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val = None
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elif val.startswith("["):
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val = [v.strip().strip('"').strip("'") for v in val.strip("[]").split(",") if v.strip()]
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fm[key] = val
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return fm if fm else None, body
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# ─── Fixers (modify content, return fixed version) ─────────────────────────
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def fix_frontmatter(content: str, domain: str, agent: str) -> tuple[str, list[str]]:
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"""Fix common frontmatter issues. Returns (fixed_content, list_of_fixes_applied)."""
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fixes = []
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fm, body = parse_frontmatter(content)
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if fm is None:
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return content, ["unfixable:no_frontmatter"]
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changed = False
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ftype = fm.get("type", "claim")
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# Fix 1: created = extraction date, always today. No parsing, no comparison.
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# "created" means "when this was extracted," period. Source publication date
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# belongs in a separate field if needed. (Ganymede review)
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today_str = date.today().isoformat()
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if ftype == "claim":
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old_created = fm.get("created")
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fm["created"] = today_str
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if old_created != today_str:
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fixes.append(f"set_created:{today_str}")
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changed = True
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# Fix 2: type field
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if "type" not in fm:
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fm["type"] = "claim"
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fixes.append("added_type:claim")
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changed = True
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# Fix 3: domain field
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if "domain" not in fm or fm["domain"] not in VALID_DOMAINS:
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fm["domain"] = domain
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fixes.append(f"fixed_domain:{fm.get('domain', 'missing')}->{domain}")
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changed = True
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# Fix 4: confidence field (claims only)
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if ftype == "claim":
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conf = fm.get("confidence")
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if conf is None:
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fm["confidence"] = "experimental"
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fixes.append("added_confidence:experimental")
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changed = True
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elif conf not in VALID_CONFIDENCE:
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fm["confidence"] = "experimental"
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fixes.append(f"fixed_confidence:{conf}->experimental")
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changed = True
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# Fix 5: description field
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if "description" not in fm or not fm["description"]:
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# Try to derive from body's first sentence
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first_sentence = body.split(".")[0].strip().lstrip("# ") if body else ""
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if first_sentence and len(first_sentence) > 10:
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fm["description"] = first_sentence[:200]
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fixes.append("derived_description_from_body")
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changed = True
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# Fix 6: source field (claims only)
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if ftype == "claim" and ("source" not in fm or not fm["source"]):
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fm["source"] = f"extraction by {agent}"
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fixes.append("added_default_source")
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changed = True
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if not changed:
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return content, []
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# Reconstruct frontmatter
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return _rebuild_content(fm, body), fixes
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def fix_wiki_links(content: str, existing_claims: set[str]) -> tuple[str, list[str]]:
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"""Fix or strip broken wiki links. Resolves slug→space mismatches before stripping.
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The LLM often generates wiki links as slugs (hyphens) but KB filenames use spaces.
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Try normalizing hyphens→spaces before giving up and stripping brackets.
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"""
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fixes = []
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# Build a lookup: normalized (lowercased, hyphens→spaces) → original stem
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_normalized_lookup: dict[str, str] = {}
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for stem in existing_claims:
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_normalized_lookup[stem.lower().replace("-", " ")] = stem
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def replace_broken(match):
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link = match.group(1).strip()
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if link in existing_claims:
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return match.group(0) # Exact match — keep as-is
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# Try normalizing slug to spaces
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normalized = link.lower().replace("-", " ")
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if normalized in _normalized_lookup:
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resolved = _normalized_lookup[normalized]
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fixes.append(f"resolved_wiki_link:{link[:40]}->{resolved[:40]}")
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return f"[[{resolved}]]"
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fixes.append(f"stripped_wiki_link:{link[:60]}")
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return link # Keep text, remove brackets
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fixed = WIKI_LINK_RE.sub(replace_broken, content)
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return fixed, fixes
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def fix_trailing_newline(content: str) -> tuple[str, list[str]]:
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"""Ensure file ends with exactly one newline."""
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if not content.endswith("\n"):
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return content + "\n", ["added_trailing_newline"]
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return content, []
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def fix_h1_title_match(content: str, filename: str) -> tuple[str, list[str]]:
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"""Ensure the content has an H1 title. Does NOT replace existing H1s.
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The H1 title in the content is authoritative — the filename is derived from it
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and may be truncated or slightly different. We only add a missing H1, never
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overwrite an existing one.
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"""
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expected_title = Path(filename).stem.replace("-", " ")
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fm, body = parse_frontmatter(content)
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if fm is None:
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return content, []
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# Find existing H1
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h1_match = re.search(r"^# (.+)$", body, re.MULTILINE)
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if h1_match:
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# H1 exists — leave it alone. The content's H1 is authoritative.
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return content, []
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elif body and not body.startswith("#"):
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# No H1 at all — add one derived from filename
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body = f"# {expected_title}\n\n{body}"
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return _rebuild_content(fm, body), ["added_h1_title"]
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return content, []
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# ─── Validators (check without modifying, return issues) ──────────────────
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def validate_claim(filename: str, content: str, existing_claims: set[str], agent: str | None = None) -> list[str]:
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"""Validate a claim file. Returns list of issues (empty = pass)."""
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issues = []
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fm, body = parse_frontmatter(content)
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if fm is None:
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return ["no_frontmatter"]
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ftype = fm.get("type", "claim")
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# Schema check
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required = REQUIRED_CLAIM_FIELDS if ftype == "claim" else REQUIRED_ENTITY_FIELDS
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for field in required:
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if field not in fm or fm[field] is None:
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issues.append(f"missing_field:{field}")
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# Domain check
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domain = fm.get("domain")
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if domain and domain not in VALID_DOMAINS:
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issues.append(f"invalid_domain:{domain}")
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# Confidence check (claims only)
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if ftype == "claim":
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conf = fm.get("confidence")
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if conf and conf not in VALID_CONFIDENCE:
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issues.append(f"invalid_confidence:{conf}")
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# Title checks (claims only, not entities)
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# Use H1 from body if available (authoritative), fall back to filename
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if ftype in ("claim", "framework"):
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h1_match = re.search(r"^# (.+)$", body, re.MULTILINE)
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title = h1_match.group(1).strip() if h1_match else Path(filename).stem.replace("-", " ")
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words = title.split()
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# Always enforce minimum 4 words — a 2-3 word title is never specific
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# enough to disagree with. (Ganymede review)
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if len(words) < 4:
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issues.append("title_too_few_words")
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elif len(words) < 8:
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# For 4-7 word titles, also require a verb/connective
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has_verb = bool(re.search(
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r"\b(is|are|was|were|will|would|can|could|should|must|has|have|had|"
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r"does|did|do|may|might|shall|"
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r"because|therefore|however|although|despite|since|through|by|"
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r"when|where|while|if|unless|"
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r"rather than|instead of|not just|more than|"
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r"\w+(?:s|ed|ing|es|tes|ses|zes|ves|cts|pts|nts|rns))\b",
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title, re.IGNORECASE,
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))
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if not has_verb:
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issues.append("title_not_proposition")
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# Description quality
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desc = fm.get("description", "")
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if isinstance(desc, str) and len(desc.strip()) < 10:
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issues.append("description_too_short")
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# Attribution check: extractor must be identified. (Leo: block extractor, warn sourcer)
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if ftype == "claim":
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from .attribution import validate_attribution
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issues.extend(validate_attribution(fm, agent=agent))
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# OPSEC check: flag claims containing dollar amounts + internal entity references.
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# Rio's rule: never extract LivingIP/Teleo deal terms to public codex. (Ganymede review)
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if ftype == "claim":
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combined_text = (title + " " + desc + " " + body).lower()
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has_dollar = bool(re.search(r"\$[\d,.]+[mkb]?\b", combined_text, re.IGNORECASE))
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has_internal = bool(re.search(
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r"\b(livingip|teleo|internal|deal terms?|valuation|equity percent)",
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combined_text, re.IGNORECASE,
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))
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if has_dollar and has_internal:
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issues.append("opsec_internal_deal_terms")
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# Body substance check (claims only)
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if ftype == "claim" and body:
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# Strip the H1 title line and check remaining content
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body_no_h1 = re.sub(r"^# .+\n*", "", body).strip()
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# Remove "Relevant Notes" and "Topics" sections
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body_content = re.split(r"\n---\n", body_no_h1)[0].strip()
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if len(body_content) < 50:
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issues.append("body_too_thin")
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# Near-duplicate check (claims only, not entities)
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if ftype != "entity":
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title_lower = Path(filename).stem.replace("-", " ").lower()
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title_words = set(title_lower.split()[:6])
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for existing in existing_claims:
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# Normalize existing stem: hyphens → spaces for consistent comparison
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existing_normalized = existing.replace("-", " ").lower()
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if len(title_words & set(existing_normalized.split()[:6])) < 2:
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continue
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ratio = SequenceMatcher(None, title_lower, existing_normalized).ratio()
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if ratio >= DEDUP_THRESHOLD:
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issues.append(f"near_duplicate:{existing[:80]}")
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break # One is enough to flag
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return issues
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# ─── Main entry point ──────────────────────────────────────────────────────
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def validate_and_fix_claims(
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claims: list[dict],
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domain: str,
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agent: str,
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existing_claims: set[str],
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repo_root: str = ".",
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) -> tuple[list[dict], list[dict], dict]:
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"""Validate and fix extracted claims. Returns (kept_claims, rejected_claims, stats).
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Each claim dict has: filename, domain, content
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Returned claims have content fixed where possible.
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Stats: {total, kept, fixed, rejected, fixes_applied: [...], rejections: [...]}
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"""
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kept = []
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rejected = []
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all_fixes = []
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all_rejections = []
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# Add intra-batch stems to existing claims (avoid false positive duplicates within same extraction)
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batch_stems = {Path(c["filename"]).stem for c in claims}
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existing_plus_batch = existing_claims | batch_stems
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for claim in claims:
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filename = claim.get("filename", "")
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content = claim.get("content", "")
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claim_domain = claim.get("domain", domain)
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if not filename or not content:
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rejected.append(claim)
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all_rejections.append(f"{filename or '?'}:missing_filename_or_content")
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continue
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# Phase 1: Apply fixers
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content, fixes1 = fix_frontmatter(content, claim_domain, agent)
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content, fixes2 = fix_wiki_links(content, existing_plus_batch)
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content, fixes3 = fix_trailing_newline(content)
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content, fixes4 = fix_h1_title_match(content, filename)
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fixes = fixes1 + fixes2 + fixes3 + fixes4
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if fixes:
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all_fixes.extend([f"{filename}:{f}" for f in fixes])
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# Phase 2: Validate (after fixes)
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issues = validate_claim(filename, content, existing_claims, agent=agent)
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# Separate hard failures from warnings
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hard_failures = [i for i in issues if not i.startswith("near_duplicate")]
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warnings = [i for i in issues if i.startswith("near_duplicate")]
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if hard_failures:
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rejected.append({**claim, "content": content, "issues": hard_failures})
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all_rejections.extend([f"{filename}:{i}" for i in hard_failures])
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else:
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if warnings:
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all_fixes.extend([f"{filename}:WARN:{w}" for w in warnings])
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kept.append({**claim, "content": content})
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stats = {
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"total": len(claims),
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"kept": len(kept),
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"fixed": len([f for f in all_fixes if ":WARN:" not in f]),
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"rejected": len(rejected),
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"fixes_applied": all_fixes,
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"rejections": all_rejections,
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}
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logger.info(
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"Post-extraction: %d/%d claims kept (%d fixed, %d rejected)",
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stats["kept"], stats["total"], stats["fixed"], stats["rejected"],
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)
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return kept, rejected, stats
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def validate_and_fix_entities(
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entities: list[dict],
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domain: str,
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existing_claims: set[str],
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) -> tuple[list[dict], list[dict], dict]:
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"""Validate and fix extracted entities. Returns (kept, rejected, stats).
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Lighter validation than claims — entities are factual records, not arguable propositions.
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"""
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kept = []
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rejected = []
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all_issues = []
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for ent in entities:
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filename = ent.get("filename", "")
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content = ent.get("content", "")
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action = ent.get("action", "create")
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if not filename:
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rejected.append(ent)
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all_issues.append("missing_filename")
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continue
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issues = []
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if action == "create" and content:
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fm, body = parse_frontmatter(content)
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if fm is None:
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issues.append("no_frontmatter")
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else:
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if fm.get("type") != "entity":
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issues.append("wrong_type")
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if "entity_type" not in fm:
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issues.append("missing_entity_type")
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if "domain" not in fm:
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issues.append("missing_domain")
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# decision_market specific checks
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if fm.get("entity_type") == "decision_market":
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for field in ("parent_entity", "platform", "category", "status"):
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if field not in fm:
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issues.append(f"dm_missing:{field}")
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# Fix trailing newline
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if content and not content.endswith("\n"):
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ent["content"] = content + "\n"
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elif action == "update":
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timeline = ent.get("timeline_entry", "")
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if not timeline:
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issues.append("update_no_timeline")
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if issues:
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rejected.append({**ent, "issues": issues})
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all_issues.extend([f"{filename}:{i}" for i in issues])
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else:
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kept.append(ent)
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stats = {
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"total": len(entities),
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"kept": len(kept),
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"rejected": len(rejected),
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"issues": all_issues,
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}
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return kept, rejected, stats
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def load_existing_claims_from_repo(repo_root: str) -> set[str]:
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"""Build set of known claim/entity stems from the repo."""
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claims: set[str] = set()
|
|
base = Path(repo_root)
|
|
for subdir in ["domains", "core", "foundations", "maps", "agents", "schemas", "entities"]:
|
|
full = base / subdir
|
|
if not full.is_dir():
|
|
continue
|
|
for f in full.rglob("*.md"):
|
|
claims.add(f.stem)
|
|
return claims
|
|
|
|
|
|
# ─── Helpers ────────────────────────────────────────────────────────────────
|
|
|
|
|
|
def _rebuild_content(fm: dict, body: str) -> str:
|
|
"""Rebuild markdown content from frontmatter dict and body."""
|
|
# Order frontmatter fields consistently
|
|
field_order = ["type", "entity_type", "name", "domain", "description",
|
|
"confidence", "source", "created", "status", "parent_entity",
|
|
"platform", "proposer", "proposal_url", "proposal_date",
|
|
"resolution_date", "category", "summary", "tracked_by",
|
|
"secondary_domains", "challenged_by"]
|
|
|
|
lines = ["---"]
|
|
written = set()
|
|
for field in field_order:
|
|
if field in fm and fm[field] is not None:
|
|
lines.append(_yaml_line(field, fm[field]))
|
|
written.add(field)
|
|
# Write remaining fields not in the order list
|
|
for key, val in fm.items():
|
|
if key not in written and val is not None:
|
|
lines.append(_yaml_line(key, val))
|
|
lines.append("---")
|
|
lines.append("")
|
|
lines.append(body)
|
|
|
|
content = "\n".join(lines)
|
|
if not content.endswith("\n"):
|
|
content += "\n"
|
|
return content
|
|
|
|
|
|
def _yaml_line(key: str, val) -> str:
|
|
"""Format a single YAML key-value line."""
|
|
if isinstance(val, dict):
|
|
# Nested YAML block (e.g. attribution with sub-keys)
|
|
lines = [f"{key}:"]
|
|
for sub_key, sub_val in val.items():
|
|
if isinstance(sub_val, list) and sub_val:
|
|
lines.append(f" {sub_key}:")
|
|
for item in sub_val:
|
|
if isinstance(item, dict):
|
|
first = True
|
|
for ik, iv in item.items():
|
|
prefix = " - " if first else " "
|
|
lines.append(f'{prefix}{ik}: "{iv}"')
|
|
first = False
|
|
else:
|
|
lines.append(f' - "{item}"')
|
|
else:
|
|
lines.append(f" {sub_key}: []")
|
|
return "\n".join(lines)
|
|
if isinstance(val, list):
|
|
return f"{key}: {json.dumps(val)}"
|
|
if isinstance(val, bool):
|
|
return f"{key}: {'true' if val else 'false'}"
|
|
if isinstance(val, (int, float)):
|
|
return f"{key}: {val}"
|
|
if isinstance(val, date):
|
|
return f"{key}: {val.isoformat()}"
|
|
# String — quote if it contains special chars
|
|
s = str(val)
|
|
if any(c in s for c in ":#{}[]|>&*!%@`"):
|
|
return f'{key}: "{s}"'
|
|
return f"{key}: {s}"
|