feat: add SQLite persistent storage for benchmark results (#26)

[Sugaria0427]

Summary

Replace flat JSON/CSV log storage with a queryable SQLite database for benchmark results, while maintaining full backward compatibility.

Related issue

Closes #26

Type of change

• API or infrastructure

How was this tested?

python tests/test_pipeline.py  (29/29 pass)
python main.py --turns 10 --checkpoints 5 10 --backends naive --log
python utils/migrate_legacy_logs.py

Checklist

• All existing tests pass
• New tests added (6 new tests)
• Docstrings added on all new public classes and functions
• Type hints used on all new function signatures
• No API key required to run any new tests
• Backward compatible — JSON/CSV output unchanged

[Neal006]

Code Review — PR #34 (SQLite persistent storage)

Thanks for the contribution! The overall design is clean and the backward-compatibility approach (JSON/CSV unchanged, SQLite as opt-in) is exactly right. I found 3 bugs that will cause crashes in production and 2 lower-priority issues that need addressing before merge.

---

🔴 Bug 1 — Duplicate results rows corrupt get_run() on run-id collision

File: utils/storage.py, save_run() (~line 1508)

self.conn.execute(
    "INSERT OR REPLACE INTO runs (run_id, timestamp, config_json) VALUES (?, ?, ?)",
    ...
)
# then: self.conn.executemany("INSERT INTO results ...", rows)

INSERT OR REPLACE replaces the row in the runs table but does not cascade-delete the existing rows in results (there is no ON DELETE CASCADE on the FK). On a second call with the same run_id (e.g., a re-run, a test cleanup failure, or the migration script running twice), results accumulates duplicate metric rows. get_run() then sees 2× the data per checkpoint and reconstructs wrong metric arrays.

Fix: delete old results before inserting new ones:

# inside `with self.conn:`, before executemany
self.conn.execute("DELETE FROM results WHERE run_id = ?", (run_id,))

Or add ON DELETE CASCADE to the FK definition and keep INSERT OR REPLACE.

---

🔴 Bug 2 — IndexError crash in _append_csv_summary when rows is empty

File: evaluation/logger.py, _append_csv_summary() (~line 442)

with open(csv_path, "a", newline="") as fh:
    writer = csv.DictWriter(fh, fieldnames=rows[0].keys())  # ← crashes if rows == []

If checkpoints is [] or every key in display_data is filtered out ("checkpoints" / "has_llm_eval"), rows is empty and rows[0] throws IndexError. The PR adds the has_llm_eval filter (good fix for the pre-existing TypeError) but still doesn't guard against empty rows.

Fix:

if not rows:
    return

Add this guard immediately before the with open(...) block.

---

🔴 Bug 3 — Storage() connections are never closed → file handle leak

File: evaluation/logger.py, log_run() and list_runs()

# log_run:
Storage().save_run(run_id, config, display_data)   # connection never closed

# list_runs:
store = Storage()
runs = store.list_runs(limit=50)
if runs:
    return runs   # returns without calling store.close()

Every call to log_run() (and every SQLite-path call to list_runs()) leaks a sqlite3.Connection. In the Streamlit dashboard, each benchmark run fires log_run and a re-render can trigger list_runs multiple times. On Windows, open SQLite file handles also block file deletion/migration.

Fix — option A (minimal): add try/finally:

# log_run:
try:
    store = Storage()
    store.save_run(run_id, config, display_data)
finally:
    store.close()

# list_runs:
try:
    store = Storage()
    runs = store.list_runs(limit=50)
    if runs:
        return runs
finally:
    store.close()

Fix — option B (cleaner): add __enter__/__exit__ to Storage so callers can use with Storage() as store:.

---

🟡 Issue 4 — get_run() returns None in metric arrays; downstream callers may crash

File: utils/storage.py, get_run() (~line 1574)

display[backend][metric] = [
    turn_map[t].get(metric) if metric in turn_map.get(t, {}) else None
    for t in cps
]

Metrics absent for a checkpoint are stored as None. compare_runs() and the dashboard iterate these arrays expecting floats. For example, compare_runs does list(v["recall"]) — that works — but any caller doing arithmetic (sum(arr), Plotly chart) on the returned list will encounter TypeError: unsupported operand type(s) for +: 'int' and 'NoneType'.

Suggested fix: filter None at the point of reconstruction, or document clearly that consumers must handle None.

---

🟡 Issue 5 — Tests leak Storage connections and use raw SQL for cleanup

File: tests/test_pipeline.py, test_logger_writes_sqlite and test_list_runs_returns_sqlite_runs

Both tests do cleanup via store.conn.execute("DELETE FROM ...") but never call store.close(). The raw-SQL cleanup also bypasses the public API, making the tests fragile if the schema changes.

Suggested fix: call store.close() in each test's finally block (consistent with the other storage tests that already do this correctly).

---

Summary table

#	Severity	File	Issue
1	🔴 High	utils/storage.py	Duplicate results rows corrupt get_run() on repeated run_id
2	🔴 High	evaluation/logger.py	IndexError when rows is empty in _append_csv_summary
3	🔴 High	evaluation/logger.py	Storage() connections never closed → file handle leak
4	🟡 Medium	utils/storage.py	None values in metric arrays break arithmetic downstream
5	🟡 Low	tests/test_pipeline.py	Integration tests leak connections and use raw SQL for cleanup

Once the three 🔴 issues are fixed I'm happy to approve. The design and test coverage are solid — these are all mechanical fixes.