Download scripts/cortex_knowledge_graph.py from Johnny5b/portable-ai-runner: direct link, hf CLI and curl.
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https://huggingface.co/datasets/Johnny5b/portable-ai-runner/resolve/main/scripts/cortex_knowledge_graph.py
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curl -L -o cortex_knowledge_graph.py https://huggingface.co/datasets/Johnny5b/portable-ai-runner/resolve/main/scripts/cortex_knowledge_graph.py
6.02 kB
| #!/usr/bin/env python3 | |
| # CORTEX knowledge graph builder — the model's map of its own knowledge. | |
| # | |
| # Reads the drive's actual artifacts (vaults, manifests, cores registry) and emits: | |
| # - knowledge_graph.json {nodes: [...], edges: [...]} | |
| # - knowledge_graph.mmd a mermaid rendering for humans | |
| # | |
| # Nodes: phases, reserved symbols, tiers/cores, models, drives, skills, stores, app. | |
| # Edges: directional pointers only — every edge says WHERE, never what to think. | |
| # | |
| # Usage: python3 cortex_knowledge_graph.py [--root <DRIVE-ROOT>] [--out <path>] | |
| # Deps: stdlib only. Run on the drive after any REPAIR to refresh the graph. | |
| import json, os, re, sys | |
| HERE = os.path.dirname(os.path.abspath(__file__)) | |
| ROOT = os.path.abspath(sys.argv[sys.argv.index("--root") + 1]) if "--root" in sys.argv else os.path.dirname(HERE) | |
| OUT = sys.argv[sys.argv.index("--out") + 1] if "--out" in sys.argv else os.path.join(ROOT, "models", "knowledge_graph.json") | |
| def load_json(path): | |
| try: | |
| with open(path, encoding="utf-8") as f: | |
| return json.load(f) | |
| except (OSError, json.JSONDecodeError): | |
| return None | |
| def load_jsonl(path): | |
| out = [] | |
| try: | |
| with open(path, encoding="utf-8") as f: | |
| for line in f: | |
| if line.strip(): | |
| out.append(json.loads(line)) | |
| except OSError: | |
| pass | |
| return out | |
| nodes, edges = [], [] | |
| _node_ids = set() | |
| def node(nid, ntype, label, **props): | |
| if nid in _node_ids: # dedupe (stores recur across maps.jsonl entries) | |
| return | |
| _node_ids.add(nid) | |
| nodes.append({"id": nid, "type": ntype, "label": label, **props}) | |
| def edge(src, dst, rel): | |
| edges.append({"src": src, "dst": dst, "rel": rel}) | |
| # ---- phases ---- | |
| for p in ["awake", "repair", "rest"]: | |
| node(f"phase:{p}", "phase", p) | |
| edges += [("phase:awake", "phase:repair", "files proposals via 'proposals' symbol"), | |
| ("phase:repair", "phase:rest", "hands over for integrity/consolidation"), | |
| ("phase:rest", "phase:awake", "re-indexed map")] | |
| # ---- reserved symbols ---- | |
| for s, desc in [("knowledge", "where to LOOK: federated index"), | |
| ("proposals", "where to PROPOSE: owner-gated queue")]: | |
| node(f"symbol:{s}", "symbol", s, desc=desc) | |
| edges += [("phase:awake", "symbol:knowledge", "looks up via"), | |
| ("phase:awake", "symbol:proposals", "files into when it cannot answer"), | |
| ("phase:repair", "symbol:proposals", "consumes after owner gate")] | |
| # ---- tiers (models/cores.json) ---- | |
| cores = load_json(os.path.join(ROOT, "models", "cores.json")) or {} | |
| tier_ids = [] | |
| for tier, info in (cores.get("tiers") or {}).items(): | |
| node(f"tier:{tier}", "tier", tier, awake_core=info.get("awake_core", "")) | |
| tier_ids.append(tier) | |
| edges.append((f"tier:{tier}", "phase:awake", "runs the same three phases")) | |
| # ---- models per tier (handles both manifest layouts) ---- | |
| MANIFESTS = [("models/models.json", "browser"), ("models/heavy.json", "heavy"), ("models/heavy70.json", "heavy70")] | |
| for rel, tier in MANIFESTS: | |
| m = load_json(os.path.join(ROOT, rel)) | |
| if not m: | |
| continue | |
| models = m.get("models") or m.get("heavy_models") or ([m["model"]] if m.get("model") else []) | |
| for mod in models: | |
| if not mod: | |
| continue | |
| mid = mod.get("gguf_repo") or mod.get("repo") or mod.get("id") or mod.get("name", "unknown") | |
| props = {} | |
| for k_src, k_out in (("gguf_file", "file"), ("file", "file"), ("size_on_disk_gb", "size_gb"), | |
| ("size_gb", "size_gb"), ("dtype", "dtype"), ("task", "task"), | |
| ("measured_gen_tok_s", "measured_gen_tok_s")): | |
| if mod.get(k_src): | |
| props[k_out] = mod[k_src] | |
| node(f"model:{mid}", "model", mid, tier=tier, **props) | |
| edges.append((f"tier:{tier}", f"model:{mid}", "awake core option")) | |
| # ---- drives, skills, stores ---- | |
| for dname in ["memories", "memories-studio"]: | |
| dpath = os.path.join(ROOT, dname) | |
| if not os.path.isdir(dpath): | |
| continue | |
| node(f"drive:{dname}", "drive", dname) | |
| edges.append(("symbol:knowledge", f"drive:{dname}", "federated index covers")) | |
| skills_dir = os.path.join(dpath, "skills") | |
| skill_files = os.listdir(skills_dir) if os.path.isdir(skills_dir) else [] | |
| for fn in skill_files: | |
| if fn.endswith(".md"): | |
| sid = f"skill:{fn[:-3]}" | |
| node(sid, "skill", fn[:-3], drive=dname) | |
| edges.append((f"drive:{dname}", sid, "holds")) | |
| edges.append(("phase:repair", sid, "acquired/patched via owner gate")) | |
| try: | |
| with open(os.path.join(dpath, "maps.jsonl"), encoding="utf-8") as f: | |
| map_entries = [json.loads(l) for l in f if l.strip()] | |
| except OSError: | |
| map_entries = [] | |
| for e in map_entries: | |
| store = e.get("store", "github-cache") | |
| node(f"store:{store}", "store", store) | |
| edges.append((f"skill:{e['skill']}", f"store:{store}", f"points_to {str(e.get('source', '?'))[:60]}")) | |
| # ---- app ---- | |
| node("app:runner", "app", "Portable AI Runner (index.html + serve.py)") | |
| for t in tier_ids: | |
| edges.append(("app:runner", f"tier:{t}", "serves")) | |
| # ---- emit ---- | |
| edges = [e if isinstance(e, dict) else {"src": e[0], "dst": e[1], "rel": e[2]} for e in edges] | |
| graph = {"generated_by": "scripts/cortex_knowledge_graph.py", "nodes": nodes, "edges": edges} | |
| os.makedirs(os.path.dirname(os.path.abspath(OUT)), exist_ok=True) | |
| with open(OUT, "w", encoding="utf-8") as f: | |
| json.dump(graph, f, indent=2) | |
| def mmd_id(nid): | |
| return re.sub(r"[^A-Za-z0-9_]", "_", nid.replace(":", "_", 1).replace(".", "_")) | |
| mmd = ["graph LR"] | |
| seen = set() | |
| for e in edges: | |
| a, b = mmd_id(e["src"]), mmd_id(e["dst"]) | |
| if (a, b) not in seen: | |
| mmd.append(f" {a}[{e['src']}] -->|{e['rel'][:40]}| {b}[{e['dst']}]") | |
| seen.add((a, b)) | |
| open(OUT[:-5] + ".mmd", "w", encoding="utf-8").write("\n".join(mmd) + "\n") | |
| print(f"knowledge graph: {len(nodes)} nodes, {len(edges)} edges -> {OUT}") |