hermes-mcp/src/hermes_mcp/store.py

from __future__ import annotations

import json
import sqlite3
from datetime import datetime, timezone
from pathlib import Path
from typing import Any

ROOT = Path(__file__).resolve().parents[2]
DATA_DIR = ROOT / "data"
DB_PATH = DATA_DIR / "hermes_mcp.sqlite3"

SCHEMA_STATEMENTS = [
    """
    create table if not exists concerns (
      id text primary key,
      account_id text,
      market_symbol text,
      base_currency text,
      quote_currency text,
      strategy_id text,
      decision_profile_id text,
      source text not null,
      status text not null default 'active',
      notes text,
      created_at text not null,
      updated_at text not null
    )
    """,
    """
    create table if not exists decision_profiles (
      id text primary key,
      name text not null,
      description text,
      config_json text not null,
      status text not null default 'active',
      created_at text not null,
      updated_at text not null
    )
    """,
    """
    create table if not exists strategy_groups (
      id text primary key,
      concern_id text not null,
      name text not null,
      strategy_family text,
      decision_profile_id text,
      notes text,
      status text not null default 'active',
      created_at text not null,
      updated_at text not null,
      foreign key(concern_id) references concerns(id) on delete cascade,
      foreign key(decision_profile_id) references decision_profiles(id)
    )
    """,
    """
    create table if not exists strategy_assignments (
      id text primary key,
      strategy_group_id text not null,
      strategy_id text not null,
      strategy_type text,
      role text,
      status text not null default 'active',
      notes text,
      created_at text not null,
      updated_at text not null,
      foreign key(strategy_group_id) references strategy_groups(id) on delete cascade
    )
    """,
    """
    create table if not exists cycles (
      id text primary key,
      started_at text not null,
      finished_at text,
      status text not null default 'running',
      trigger text not null,
      notes text
    )
    """,
    """
    create table if not exists observations (
      id text primary key,
      cycle_id text not null,
      concern_id text,
      source text not null,
      kind text not null,
      payload_json text not null,
      observed_at text not null,
      foreign key(cycle_id) references cycles(id),
      foreign key(concern_id) references concerns(id)
    )
    """,
    """
    create table if not exists states (
      id text primary key,
      cycle_id text not null,
      concern_id text not null,
      market_regime text,
      volatility_state text,
      liquidity_state text,
      sentiment_pressure text,
      event_risk text,
      execution_quality text,
      confidence real,
      payload_json text not null,
      created_at text not null,
      foreign key(cycle_id) references cycles(id),
      foreign key(concern_id) references concerns(id)
    )
    """,
    """
    create table if not exists narratives (
      id text primary key,
      cycle_id text not null,
      concern_id text not null,
      summary text not null,
      key_drivers_json text not null,
      risk_flags_json text not null,
      uncertainties_json text not null,
      confidence real,
      created_at text not null,
      foreign key(cycle_id) references cycles(id),
      foreign key(concern_id) references concerns(id)
    )
    """,
    """
    create table if not exists decisions (
      id text primary key,
      cycle_id text not null,
      concern_id text not null,
      mode text not null,
      action text not null,
      target_strategy text,
      target_policy_json text,
      reason_summary text,
      confidence real,
      requires_action integer not null default 0,
      created_at text not null,
      foreign key(cycle_id) references cycles(id),
      foreign key(concern_id) references concerns(id)
    )
    """,
    """
    create table if not exists actions (
      id text primary key,
      decision_id text not null,
      target text not null,
      command text not null,
      request_json text not null,
      response_json text,
      status text not null default 'pending',
      executed_at text,
      foreign key(decision_id) references decisions(id)
    )
    """,
    """
    create table if not exists coverage_gaps (
      id text primary key,
      cycle_id text not null,
      concern_id text,
      gap_type text not null,
      summary text not null,
      recommendation_json text not null,
      status text not null default 'open',
      created_at text not null,
      foreign key(cycle_id) references cycles(id),
      foreign key(concern_id) references concerns(id)
    )
    """,
    """
    create table if not exists regime_samples (
      id text primary key,
      cycle_id text not null,
      concern_id text not null,
      timeframe text not null,
      regime_json text not null,
      captured_at text not null,
      foreign key(cycle_id) references cycles(id),
      foreign key(concern_id) references concerns(id)
    )
    """,
    "create index if not exists idx_observations_cycle on observations(cycle_id)",
    "create index if not exists idx_observations_concern on observations(concern_id)",
    "create index if not exists idx_concerns_profile on concerns(decision_profile_id)",
    "create index if not exists idx_decision_profiles_status on decision_profiles(status)",
    "create index if not exists idx_strategy_groups_concern on strategy_groups(concern_id)",
    "create index if not exists idx_strategy_groups_profile on strategy_groups(decision_profile_id)",
    "create index if not exists idx_strategy_assignments_group on strategy_assignments(strategy_group_id)",
    "create index if not exists idx_strategy_assignments_strategy on strategy_assignments(strategy_id)",
    "create index if not exists idx_states_cycle on states(cycle_id)",
    "create index if not exists idx_states_concern on states(concern_id)",
    "create index if not exists idx_narratives_cycle on narratives(cycle_id)",
    "create index if not exists idx_decisions_cycle on decisions(cycle_id)",
    "create index if not exists idx_actions_decision on actions(decision_id)",
    "create index if not exists idx_gaps_cycle on coverage_gaps(cycle_id)",
    "create index if not exists idx_regime_samples_concern on regime_samples(concern_id)",
]


def _now() -> str:
    return datetime.now(timezone.utc).isoformat()


def _connect() -> sqlite3.Connection:
    DATA_DIR.mkdir(parents=True, exist_ok=True)
    conn = sqlite3.connect(DB_PATH)
    conn.row_factory = sqlite3.Row
    conn.execute("pragma foreign_keys = on")
    return conn


def init_db() -> None:
    with _connect() as conn:
        for stmt in SCHEMA_STATEMENTS:
            if stmt.lstrip().lower().startswith("create index"):
                continue
            conn.execute(stmt)
        conn.execute(
            """
            create table if not exists state (
              key text primary key,
              value text not null,
              updated_at text not null default current_timestamp
            )
            """
            )

        concern_columns = {row[1] for row in conn.execute("pragma table_info(concerns)").fetchall()}
        for column in ("base_currency", "quote_currency", "decision_profile_id"):
            if column not in concern_columns:
                conn.execute(f"alter table concerns add column {column} text")

        for stmt in SCHEMA_STATEMENTS:
            if not stmt.lstrip().lower().startswith("create index"):
                continue
            conn.execute(stmt)


def get_state() -> dict[str, Any]:
    init_db()
    with _connect() as conn:
        row = conn.execute("select value from state where key = ?", ("snapshot",)).fetchone()
        if not row:
            return {
                "status": "stub",
                "thinking": "Hermes is scaffolded and waiting for integrations.",
                "layers": ["concerns", "decision_profiles", "strategy_groups", "strategy_assignments", "cycles", "observations", "states", "narratives", "decisions", "actions", "coverage_gaps"],
            }
        return json.loads(row["value"])


def put_state(payload: dict[str, Any]) -> None:
    init_db()
    with _connect() as conn:
        conn.execute(
            "insert into state(key, value, updated_at) values(?, ?, current_timestamp) on conflict(key) do update set value=excluded.value, updated_at=current_timestamp",
            ("snapshot", json.dumps(payload)),
        )


def upsert_concern(*, id: str, account_id: str | None, market_symbol: str | None, base_currency: str | None = None, quote_currency: str | None = None, strategy_id: str | None, decision_profile_id: str | None = None, source: str, status: str = "active", notes: str | None = None) -> None:
    init_db()
    now = _now()
    with _connect() as conn:
        conn.execute(
            """
            insert into concerns(id, account_id, market_symbol, base_currency, quote_currency, strategy_id, decision_profile_id, source, status, notes, created_at, updated_at)
            values(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
            on conflict(id) do update set
              account_id=excluded.account_id,
              market_symbol=excluded.market_symbol,
              base_currency=excluded.base_currency,
              quote_currency=excluded.quote_currency,
              strategy_id=excluded.strategy_id,
              decision_profile_id=excluded.decision_profile_id,
              source=excluded.source,
              status=excluded.status,
              notes=excluded.notes,
              updated_at=excluded.updated_at
            """,
            (id, account_id, market_symbol, base_currency, quote_currency, strategy_id, decision_profile_id, source, status, notes, now, now),
        )


def list_concerns() -> list[dict[str, Any]]:
    init_db()
    with _connect() as conn:
        rows = conn.execute("select * from concerns order by updated_at desc").fetchall()
    return [dict(r) for r in rows]


def upsert_decision_profile(*, id: str, name: str, config: dict[str, Any], description: str | None = None, status: str = "active") -> None:
    init_db()
    now = _now()
    with _connect() as conn:
        conn.execute(
            """
            insert into decision_profiles(id, name, description, config_json, status, created_at, updated_at)
            values(?, ?, ?, ?, ?, ?, ?)
            on conflict(id) do update set
              name=excluded.name,
              description=excluded.description,
              config_json=excluded.config_json,
              status=excluded.status,
              updated_at=excluded.updated_at
            """,
            (id, name, description, json.dumps(config, ensure_ascii=False), status, now, now),
        )


def list_decision_profiles() -> list[dict[str, Any]]:
    init_db()
    with _connect() as conn:
        rows = conn.execute("select * from decision_profiles order by updated_at desc").fetchall()
    return [dict(r) for r in rows]


def get_decision_profile(*, profile_id: str) -> dict[str, Any] | None:
    init_db()
    profile_id = str(profile_id or "").strip()
    if not profile_id:
        return None
    with _connect() as conn:
        row = conn.execute("select * from decision_profiles where id = ?", (profile_id,)).fetchone()
    return dict(row) if row else None


def upsert_strategy_group(*, id: str, concern_id: str, name: str, strategy_family: str | None = None, decision_profile_id: str | None = None, notes: str | None = None, status: str = "active") -> None:
    init_db()
    now = _now()
    with _connect() as conn:
        conn.execute(
            """
            insert into strategy_groups(id, concern_id, name, strategy_family, decision_profile_id, notes, status, created_at, updated_at)
            values(?, ?, ?, ?, ?, ?, ?, ?, ?)
            on conflict(id) do update set
              concern_id=excluded.concern_id,
              name=excluded.name,
              strategy_family=excluded.strategy_family,
              decision_profile_id=excluded.decision_profile_id,
              notes=excluded.notes,
              status=excluded.status,
              updated_at=excluded.updated_at
            """,
            (id, concern_id, name, strategy_family, decision_profile_id, notes, status, now, now),
        )


def list_strategy_groups(*, concern_id: str | None = None) -> list[dict[str, Any]]:
    init_db()
    with _connect() as conn:
        if concern_id:
            rows = conn.execute("select * from strategy_groups where concern_id = ? order by updated_at desc", (concern_id,)).fetchall()
        else:
            rows = conn.execute("select * from strategy_groups order by updated_at desc").fetchall()
    return [dict(r) for r in rows]


def upsert_strategy_assignment(*, id: str, strategy_group_id: str, strategy_id: str, strategy_type: str | None = None, role: str | None = None, status: str = "active", notes: str | None = None) -> None:
    init_db()
    now = _now()
    with _connect() as conn:
        conn.execute(
            """
            insert into strategy_assignments(id, strategy_group_id, strategy_id, strategy_type, role, status, notes, created_at, updated_at)
            values(?, ?, ?, ?, ?, ?, ?, ?, ?)
            on conflict(id) do update set
              strategy_group_id=excluded.strategy_group_id,
              strategy_id=excluded.strategy_id,
              strategy_type=excluded.strategy_type,
              role=excluded.role,
              status=excluded.status,
              notes=excluded.notes,
              updated_at=excluded.updated_at
            """,
            (id, strategy_group_id, strategy_id, strategy_type, role, status, notes, now, now),
        )


def list_strategy_assignments(*, strategy_group_id: str | None = None) -> list[dict[str, Any]]:
    init_db()
    with _connect() as conn:
        if strategy_group_id:
            rows = conn.execute("select * from strategy_assignments where strategy_group_id = ? order by updated_at desc", (strategy_group_id,)).fetchall()
        else:
            rows = conn.execute("select * from strategy_assignments order by updated_at desc").fetchall()
    return [dict(r) for r in rows]


def delete_concern(*, concern_id: str) -> dict[str, int]:
    init_db()
    concern_id = str(concern_id or "").strip()
    if not concern_id:
        return {"concerns": 0, "strategy_groups": 0, "strategy_assignments": 0, "observations": 0, "states": 0, "narratives": 0, "decisions": 0, "actions": 0, "coverage_gaps": 0, "regime_samples": 0}

    deleted = {"concerns": 0, "strategy_groups": 0, "strategy_assignments": 0, "observations": 0, "states": 0, "narratives": 0, "decisions": 0, "actions": 0, "coverage_gaps": 0, "regime_samples": 0}
    with _connect() as conn:
        decision_ids = [row[0] for row in conn.execute("select id from decisions where concern_id = ?", (concern_id,)).fetchall()]
        group_ids = [row[0] for row in conn.execute("select id from strategy_groups where concern_id = ?", (concern_id,)).fetchall()]
        deleted["actions"] = conn.execute(
            f"delete from actions where decision_id in ({','.join('?' for _ in decision_ids)})",
            decision_ids,
        ).rowcount if decision_ids else 0
        deleted["strategy_assignments"] = conn.execute(
            f"delete from strategy_assignments where strategy_group_id in ({','.join('?' for _ in group_ids)})",
            group_ids,
        ).rowcount if group_ids else 0
        deleted["strategy_groups"] = conn.execute("delete from strategy_groups where concern_id = ?", (concern_id,)).rowcount or 0
        deleted["observations"] = conn.execute("delete from observations where concern_id = ?", (concern_id,)).rowcount or 0
        deleted["states"] = conn.execute("delete from states where concern_id = ?", (concern_id,)).rowcount or 0
        deleted["narratives"] = conn.execute("delete from narratives where concern_id = ?", (concern_id,)).rowcount or 0
        deleted["coverage_gaps"] = conn.execute("delete from coverage_gaps where concern_id = ?", (concern_id,)).rowcount or 0
        deleted["regime_samples"] = conn.execute("delete from regime_samples where concern_id = ?", (concern_id,)).rowcount or 0
        deleted["decisions"] = conn.execute("delete from decisions where concern_id = ?", (concern_id,)).rowcount or 0
        deleted["concerns"] = conn.execute("delete from concerns where id = ?", (concern_id,)).rowcount or 0
    return deleted


def prune_older_than(days: int) -> dict[str, int]:
    init_db()
    cutoff = datetime.now(timezone.utc).timestamp() - (days * 86400)
    cutoff_iso = datetime.fromtimestamp(cutoff, tz=timezone.utc).isoformat()
    with _connect() as conn:
        deleted = {}
        for table in ("actions", "decisions", "narratives", "states", "observations", "coverage_gaps", "cycles"):
            if table == "actions":
                where = "executed_at is not null and executed_at < ?"
            elif table in {"decisions", "narratives", "states", "observations", "coverage_gaps", "cycles"}:
                where = "created_at < ?" if table != "cycles" else "started_at < ?"
            else:
                continue
            cur = conn.execute(f"delete from {table} where {where}", (cutoff_iso,))
            deleted[table] = cur.rowcount if cur.rowcount is not None else 0
    return deleted


def sync_concerns_from_strategies(strategies: list[dict[str, Any]]) -> list[dict[str, Any]]:
    seen: set[str] = set()
    synced: list[dict[str, Any]] = []
    existing = {str(c.get("id") or ""): c for c in list_concerns()}
    for s in strategies:
        account_id = str(s.get("account_id") or "").strip() or None
        market_symbol = str(s.get("market_symbol") or "").strip() or None
        base_currency = str(s.get("base_currency") or "").strip() or None
        quote_currency = str(s.get("counter_currency") or s.get("quote_currency") or "").strip() or None
        strategy_id = str(s.get("id") or s.get("name") or s.get("strategy_type") or "").strip() or None
        if not account_id or not market_symbol:
            continue
        concern_id = f"{account_id}:{market_symbol}"
        if concern_id in seen:
            continue
        seen.add(concern_id)
        current = existing.get(concern_id, {})
        upsert_concern(
            id=concern_id,
            account_id=account_id,
            market_symbol=market_symbol,
            base_currency=base_currency,
            quote_currency=quote_currency,
            strategy_id=strategy_id,
            decision_profile_id=str(current.get("decision_profile_id") or "").strip() or None,
            source=str(current.get("source") or "trader_inventory"),
            status=str(current.get("status") or "active"),
            notes=str(current.get("notes") or "mirrored from trader strategy inventory").strip() or None,
        )
        synced.append({"id": concern_id, "account_id": account_id, "market_symbol": market_symbol, "base_currency": base_currency, "quote_currency": quote_currency, "strategy_id": strategy_id})
    return synced


def table_counts() -> dict[str, int]:
    init_db()
    tables = ["concerns", "decision_profiles", "strategy_groups", "strategy_assignments", "cycles", "observations", "states", "narratives", "decisions", "actions", "coverage_gaps", "regime_samples"]
    out: dict[str, int] = {}
    with _connect() as conn:
        for table in tables:
            out[table] = int(conn.execute(f"select count(*) as n from {table}").fetchone()["n"])
    return out


def latest_cycle() -> dict[str, Any] | None:
    init_db()
    with _connect() as conn:
        row = conn.execute("select * from cycles order by started_at desc limit 1").fetchone()
    return dict(row) if row else None


def latest_cycles(limit: int = 20) -> list[dict[str, Any]]:
    init_db()
    with _connect() as conn:
        rows = conn.execute("select * from cycles order by started_at desc limit ?", (limit,)).fetchall()
    return [dict(r) for r in rows]


def upsert_cycle(*, id: str, started_at: str, finished_at: str | None, status: str, trigger: str, notes: str | None = None) -> None:
    init_db()
    with _connect() as conn:
        conn.execute(
            """
            insert into cycles(id, started_at, finished_at, status, trigger, notes)
            values(?, ?, ?, ?, ?, ?)
            on conflict(id) do update set
              started_at=excluded.started_at,
              finished_at=excluded.finished_at,
              status=excluded.status,
              trigger=excluded.trigger,
              notes=excluded.notes
            """,
            (id, started_at, finished_at, status, trigger, notes),
        )


def upsert_regime_sample(*, id: str, cycle_id: str, concern_id: str, timeframe: str, regime_json: str, captured_at: str) -> None:
    init_db()
    with _connect() as conn:
        conn.execute(
            """
            insert into regime_samples(id, cycle_id, concern_id, timeframe, regime_json, captured_at)
            values(?, ?, ?, ?, ?, ?)
            on conflict(id) do update set
              cycle_id=excluded.cycle_id,
              concern_id=excluded.concern_id,
              timeframe=excluded.timeframe,
              regime_json=excluded.regime_json,
              captured_at=excluded.captured_at
            """,
            (id, cycle_id, concern_id, timeframe, regime_json, captured_at),
        )


def upsert_observation(*, id: str, cycle_id: str, concern_id: str | None, source: str, kind: str, payload_json: str, observed_at: str | None = None) -> None:
    init_db()
    observed_at = observed_at or _now()
    with _connect() as conn:
        conn.execute(
            """
            insert into observations(id, cycle_id, concern_id, source, kind, payload_json, observed_at)
            values(?, ?, ?, ?, ?, ?, ?)
            on conflict(id) do update set
              cycle_id=excluded.cycle_id,
              concern_id=excluded.concern_id,
              source=excluded.source,
              kind=excluded.kind,
              payload_json=excluded.payload_json,
              observed_at=excluded.observed_at
            """,
            (id, cycle_id, concern_id, source, kind, payload_json, observed_at),
        )


def upsert_state(*, id: str, cycle_id: str, concern_id: str, market_regime: str | None, volatility_state: str | None, liquidity_state: str | None, sentiment_pressure: str | None, event_risk: str | None, execution_quality: str | None, confidence: float | None, payload_json: str, created_at: str | None = None) -> None:
    init_db()
    created_at = created_at or _now()
    with _connect() as conn:
        conn.execute(
            """
            insert into states(id, cycle_id, concern_id, market_regime, volatility_state, liquidity_state, sentiment_pressure, event_risk, execution_quality, confidence, payload_json, created_at)
            values(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
            on conflict(id) do update set
              cycle_id=excluded.cycle_id,
              concern_id=excluded.concern_id,
              market_regime=excluded.market_regime,
              volatility_state=excluded.volatility_state,
              liquidity_state=excluded.liquidity_state,
              sentiment_pressure=excluded.sentiment_pressure,
              event_risk=excluded.event_risk,
              execution_quality=excluded.execution_quality,
              confidence=excluded.confidence,
              payload_json=excluded.payload_json,
              created_at=excluded.created_at
            """,
            (id, cycle_id, concern_id, market_regime, volatility_state, liquidity_state, sentiment_pressure, event_risk, execution_quality, confidence, payload_json, created_at),
        )


def upsert_narrative(*, id: str, cycle_id: str, concern_id: str, summary: str, key_drivers_json: str, risk_flags_json: str, uncertainties_json: str, confidence: float | None, created_at: str | None = None) -> None:
    init_db()
    created_at = created_at or _now()
    with _connect() as conn:
        conn.execute(
            """
            insert into narratives(id, cycle_id, concern_id, summary, key_drivers_json, risk_flags_json, uncertainties_json, confidence, created_at)
            values(?, ?, ?, ?, ?, ?, ?, ?, ?)
            on conflict(id) do update set
              cycle_id=excluded.cycle_id,
              concern_id=excluded.concern_id,
              summary=excluded.summary,
              key_drivers_json=excluded.key_drivers_json,
              risk_flags_json=excluded.risk_flags_json,
              uncertainties_json=excluded.uncertainties_json,
              confidence=excluded.confidence,
              created_at=excluded.created_at
            """,
            (id, cycle_id, concern_id, summary, key_drivers_json, risk_flags_json, uncertainties_json, confidence, created_at),
        )


def upsert_decision(*, id: str, cycle_id: str, concern_id: str, mode: str, action: str, target_strategy: str | None, target_policy_json: str | None, reason_summary: str | None, confidence: float | None, requires_action: bool, created_at: str | None = None) -> None:
    init_db()
    created_at = created_at or _now()
    with _connect() as conn:
        conn.execute(
            """
            insert into decisions(id, cycle_id, concern_id, mode, action, target_strategy, target_policy_json, reason_summary, confidence, requires_action, created_at)
            values(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
            on conflict(id) do update set
              cycle_id=excluded.cycle_id,
              concern_id=excluded.concern_id,
              mode=excluded.mode,
              action=excluded.action,
              target_strategy=excluded.target_strategy,
              target_policy_json=excluded.target_policy_json,
              reason_summary=excluded.reason_summary,
              confidence=excluded.confidence,
              requires_action=excluded.requires_action,
              created_at=excluded.created_at
            """,
            (id, cycle_id, concern_id, mode, action, target_strategy, target_policy_json, reason_summary, confidence, 1 if requires_action else 0, created_at),
        )


def latest_states(limit: int = 20) -> list[dict[str, Any]]:
    init_db()
    with _connect() as conn:
        rows = conn.execute("select * from states order by created_at desc limit ?", (limit,)).fetchall()
    return [dict(r) for r in rows]


def recent_states_for_concern(*, concern_id: str, since_seconds: int, limit: int = 24) -> list[dict[str, Any]]:
    init_db()
    cutoff = datetime.now(timezone.utc).timestamp() - max(1, since_seconds)
    cutoff_iso = datetime.fromtimestamp(cutoff, tz=timezone.utc).isoformat()
    with _connect() as conn:
        rows = conn.execute(
            "select * from states where concern_id = ? and created_at >= ? order by created_at asc limit ?",
            (concern_id, cutoff_iso, limit),
        ).fetchall()
    return [dict(r) for r in rows]


def latest_decisions(limit: int = 20) -> list[dict[str, Any]]:
    init_db()
    with _connect() as conn:
        rows = conn.execute("select * from decisions order by created_at desc limit ?", (limit,)).fetchall()
    return [dict(r) for r in rows]


def latest_narratives(limit: int = 20) -> list[dict[str, Any]]:
    init_db()
    with _connect() as conn:
        rows = conn.execute("select * from narratives order by created_at desc limit ?", (limit,)).fetchall()
    return [dict(r) for r in rows]


def latest_regime_samples(limit: int = 20) -> list[dict[str, Any]]:
    init_db()
    with _connect() as conn:
        rows = conn.execute("select * from regime_samples order by captured_at desc limit ?", (limit,)).fetchall()
    return [dict(r) for r in rows]


def latest_observations(limit: int = 20, source: str | None = None) -> list[dict[str, Any]]:
    init_db()
    with _connect() as conn:
        if source:
            rows = conn.execute(
                "select * from observations where source = ? order by observed_at desc limit ?",
                (source, limit),
            ).fetchall()
        else:
            rows = conn.execute("select * from observations order by observed_at desc limit ?", (limit,)).fetchall()
    return [dict(r) for r in rows]


def recent_regime_samples(limit: int = 200) -> list[dict[str, Any]]:
    init_db()
    with _connect() as conn:
        rows = conn.execute("select * from regime_samples order by captured_at desc limit ?", (limit,)).fetchall()
    return [dict(r) for r in rows]