portable-ai-runner / scripts /build_knowledge_vault.py
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r6: scripts/build_knowledge_vault.py (gate fix)
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#!/usr/bin/env python3
"""CORTEX knowledge-vault builder v3 — owner directive execution:
clone approved skill repos -> /modules/, AST-extract -> /symbols/schemas/,
sha256 manifests, merge real entries into symbol_evolution_index.json, upload tree.
"""
import ast, hashlib, json, os, subprocess, time
REPO = "Johnny5b/portable-ai-runner"
BASE = "/work"
MODULES = os.path.join(BASE, "modules")
SCHEMAS = os.path.join(BASE, "schemas_out")
SKILLS = [
("EVO_TREE:TINYVERSE", "TinyverseGP", "https://github.com/GPBench/TinyverseGP.git"),
("EVO_OPT:DEAP", "deap", "https://github.com/deap/deap.git"),
("EVO_NEURO:EVOTORCH", "evotorch", "https://github.com/nnaisense/evotorch.git"),
("AGENT:EVA", "eva-evolutional-agent","https://github.com/arturkorb3/eva-evolutional-agent.git"),
("RHETORIC:RST", "isanlp_rst", "https://github.com/tchewik/isanlp_rst.git"),
("RHETORIC:ARG_MINER", "e2e-microtexts", "https://github.com/tchewik/e2e-microtexts.git"),
]
MAX_UPLOAD_BYTES = 20 * 1024 * 1024
MAX_PARSE_BYTES = 300 * 1024
def sh(cmd, cwd=None):
"""cmd: list -> no shell; str -> shell. Never mix."""
if isinstance(cmd, list):
r = subprocess.run(cmd, cwd=cwd, capture_output=True, text=True, timeout=900)
else:
r = subprocess.run(cmd, shell=True, cwd=cwd, capture_output=True, text=True, timeout=900)
return r.returncode, (r.stdout or "") + (r.stderr or "")
def sha256(path):
h = hashlib.sha256()
with open(path, "rb") as f:
for chunk in iter(lambda: f.read(1 << 20), b""):
h.update(chunk)
return h.hexdigest()
def clone(url, dest):
if os.path.exists(dest):
return sh("git rev-parse HEAD", cwd=dest)[1].strip()
code, out = sh(["git", "clone", "--depth", "1", url, dest])
if code != 0:
raise RuntimeError(f"clone failed {url}: {out[-300:]}")
return sh("git rev-parse HEAD", cwd=dest)[1].strip()
def walk_files(root):
for dirpath, _, files in os.walk(root):
if ".git" in dirpath:
continue
for fn in files:
yield os.path.join(dirpath, fn)
def parse_module(name, root):
fns, classes, nfiles = [], [], 0
for p in walk_files(root):
if not p.endswith(".py") or os.path.getsize(p) > MAX_PARSE_BYTES:
continue
nfiles += 1
try:
src = open(p, encoding="utf-8", errors="ignore").read()
tree = ast.parse(src)
except SyntaxError:
continue
rel = os.path.relpath(p, root)
for node in tree.body:
if isinstance(node, ast.FunctionDef):
fns.append({"file": rel, "name": node.name,
"args": [a.arg for a in node.args.args],
"doc": (ast.get_docstring(node) or "")[:160]})
elif isinstance(node, ast.ClassDef):
ms = [m.name for m in node.body if isinstance(m, ast.FunctionDef)]
classes.append({"file": rel, "name": node.name, "methods": ms,
"doc": (ast.get_docstring(node) or "")[:160]})
return {"module": name, "files_parsed": nfiles, "functions": fns, "classes": classes}, fns, classes
def templates_md(name, fns, classes, commit):
L = [f"# {name} — execution schema",
f"upstream commit: `{commit}` | extractor: stdlib `ast` (no the banned library (owner directive 2026-09-18))",
f"{len(fns)} functions, {len(classes)} classes parsed", "",
"## Function signatures"]
for f in fns[:80]:
sig = ", ".join(f["args"]) or "()"
L.append(f"- `{f['name']}({sig})` — {f['file']}" + (f" · {f['doc']}" if f["doc"] else ""))
if len(fns) > 80:
L.append(f"- … and {len(fns) - 80} more (see {name}.json)")
L += ["", "## Classes"]
for c in classes[:60]:
L.append(f"- `{c['name']}` ({len(c['methods'])} methods) — {c['file']}")
return "\n".join(L) + "\n"
def file_manifest(root):
out = {}
for p in walk_files(root):
if os.path.getsize(p) <= MAX_UPLOAD_BYTES:
out[os.path.relpath(p, root)] = sha256(p)
return out
def main():
from huggingface_hub import HfApi, hf_hub_download
token = os.environ["HF_TOKEN"]
api = HfApi(token=token)
os.makedirs(MODULES, exist_ok=True)
os.makedirs(SCHEMAS, exist_ok=True)
entries = {}
for sym, name, url in SKILLS:
t0 = time.time()
dest = os.path.join(MODULES, name)
commit = sh("git rev-parse HEAD", cwd=dest)[1].strip() if os.path.exists(dest) else clone(url, dest)
parsed, fns, classes = parse_module(name, dest)
json.dump(parsed, open(os.path.join(SCHEMAS, f"{name}.json"), "w"), indent=1)
open(os.path.join(SCHEMAS, f"{name}.md"), "w").write(templates_md(name, fns, classes, commit))
man = file_manifest(dest)
json.dump({"module": name, "commit": commit, "files": len(man), "sha256": man},
open(os.path.join(SCHEMAS, f"{name}.manifest.json"), "w"))
print(f"[OK] {name} symbol:{sym} commit={commit[:12]} files={len(man)} "
f"parsed={len(fns)}f/{len(classes)}c in {time.time() - t0:.0f}s", flush=True)
entries[name] = {"symbol": f"symbol:{sym}", "type": "skill_module",
"path": f"modules/{name}", "upstream": url, "commit": commit,
"schema_md": f"symbols/schemas/{name}.md",
"schema_json": f"symbols/schemas/{name}.json",
"manifest": f"symbols/schemas/{name}.manifest.json",
"status": "active-mirror"}
idx_path = hf_hub_download(REPO, "symbols/symbol_evolution_index.json",
repo_type="dataset", token=token)
idx = json.load(open(idx_path))
idx.setdefault("symbols", {})
for k, v in entries.items():
idx["symbols"][f"symbol:MODULE:{k}"] = v
idx["last_build"] = {"ts": time.time(), "builder": "scripts/build_knowledge_vault.py v3",
"modules": sorted(entries)}
json.dump(idx, open(idx_path, "w"), indent=2)
for name in entries:
api.upload_folder(repo_id=REPO, repo_type="dataset",
folder_path=os.path.join(MODULES, name),
path_in_repo=f"modules/{name}",
commit_message=f"CORTEX vault: module {name} (active-mirror)")
print(f"[UP] modules/{name}", flush=True)
api.upload_folder(repo_id=REPO, repo_type="dataset", folder_path=SCHEMAS,
path_in_repo="symbols/schemas",
commit_message="CORTEX vault: AST-extracted schemas")
api.upload_file(repo_id=REPO, repo_type="dataset", path_or_fileobj=idx_path,
path_in_repo="symbols/symbol_evolution_index.json",
commit_message="CORTEX vault: symbol index with sha256 manifests")
print(f"BUILD DONE modules={len(entries)}", flush=True)
if __name__ == "__main__":
main()