| """ |
| Extract all post + comment text from every valid sweep DB and tag each row |
| with (model, persona, run, mode, kind). Writes a single JSONL. |
| |
| Validity criterion matches persona_variance: nc>=200 & nu>=26 (for tri) or |
| nu>=18 (dyad), and metadata + good model map. |
| """ |
| import json |
| import sqlite3 |
| import sys |
| from collections import defaultdict |
| from pathlib import Path |
|
|
| RUNS = Path("runs") |
| OUT = Path("data/texts.jsonl") |
|
|
| SHORT = { |
| "Qwen/Qwen3-32B": "Qwen", |
| "openai/gpt-oss-20b": "gpt-oss", |
| "mistralai/Magistral-Small-2509": "Mag", |
| "zai-org/GLM-4-32B-0414": "GLM-4", |
| "google/gemma-4-31B-it": "Gemma", |
| } |
|
|
|
|
| def load_valid_runs(): |
| rows = [] |
| n_db = n_valid = 0 |
| for db in sorted(RUNS.glob("sweep_*.db")): |
| name = db.name |
| if any(x in name for x in ["archive", "snapshot", "olm", "hermes", "qwq", "glm47", "pilot_"]): |
| continue |
| meta_p = str(db).replace(".db", ".metadata.json") |
| if not Path(meta_p).exists(): |
| continue |
| n_db += 1 |
| try: |
| meta = json.load(open(meta_p)) |
| except Exception: |
| continue |
| amm = meta.get("agent_model_map", {}) |
| if not amm: |
| continue |
| uid_to_model = {int(k) + 1: SHORT.get(v["model"]) for k, v in amm.items()} |
| if any(v is None for v in uid_to_model.values()): |
| continue |
| mode = "tri" if "tri_" in name else "dyad" |
| threshold = 26 if mode == "tri" else 18 |
| try: |
| c = sqlite3.connect(db) |
| nu = c.execute("SELECT COUNT(DISTINCT user_id) FROM comment").fetchone()[0] |
| nc = c.execute("SELECT COUNT(*) FROM comment").fetchone()[0] |
| if nu < threshold or nc < 200: |
| c.close() |
| continue |
| users = {uid: uname for uid, uname in c.execute("SELECT user_id, user_name FROM user").fetchall()} |
| posts = c.execute("SELECT post_id, user_id, content FROM post").fetchall() |
| comments = c.execute("SELECT comment_id, user_id, content FROM comment").fetchall() |
| c.close() |
| except Exception as e: |
| print(f"err {name}: {e}", file=sys.stderr) |
| continue |
| n_valid += 1 |
| run_id = db.stem |
| for pid, uid, content in posts: |
| if not content: |
| continue |
| rows.append({ |
| "run": run_id, "mode": mode, "kind": "post", |
| "model": uid_to_model.get(uid), "persona": users.get(uid, f"u{uid}"), |
| "text": content, |
| }) |
| for cid, uid, content in comments: |
| if not content: |
| continue |
| rows.append({ |
| "run": run_id, "mode": mode, "kind": "comment", |
| "model": uid_to_model.get(uid), "persona": users.get(uid, f"u{uid}"), |
| "text": content, |
| }) |
| return rows, n_db, n_valid |
|
|
|
|
| def main(): |
| rows, n_db, n_valid = load_valid_runs() |
| OUT.parent.mkdir(parents=True, exist_ok=True) |
| with open(OUT, "w") as f: |
| for r in rows: |
| f.write(json.dumps(r, ensure_ascii=False) + "\n") |
| by_model = defaultdict(lambda: [0, 0]) |
| by_kind = defaultdict(int) |
| for r in rows: |
| by_model[r["model"]][0 if r["kind"] == "post" else 1] += 1 |
| by_kind[r["kind"]] += 1 |
| print(f"DBs scanned: {n_db} valid: {n_valid} rows: {len(rows):,}") |
| print(f"by kind: {dict(by_kind)}") |
| print("by model (posts, comments):") |
| for m, (p, cm) in sorted(by_model.items()): |
| print(f" {m:10s} posts={p:6d} comments={cm:6d}") |
| print(f"wrote {OUT}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
