OpenFin/backend/routers/pattern_lab.py

"""
Pattern Lab router — historical backtest for pattern discovery.
Prefix: /api/pattern-lab
"""
import json
import uuid
from datetime import datetime
from typing import Optional, List

from fastapi import APIRouter, HTTPException, BackgroundTasks
from pydantic import BaseModel

from services.database import get_conn, get_config, save_custom_pattern

router = APIRouter(prefix="/api/pattern-lab", tags=["pattern-lab"])


# ── Pydantic models ────────────────────────────────────────────────────────────

class RunRequest(BaseModel):
    preset_id: Optional[str] = None
    theme: str
    analysis_date: str          # YYYY-MM-DD
    horizon_days: int = 90
    assets: List[str]
    theme_hint: str


class EvaluateRequest(BaseModel):
    pass


class SavePatternRequest(BaseModel):
    run_id: str
    pattern_index: int
    name: Optional[str] = None
    category: Optional[str] = None
    signal_direction: Optional[str] = None
    asset_class: Optional[str] = "indices"


class InstrumentScanRequest(BaseModel):
    ticker: str
    instrument_name: str
    start_date: str       # YYYY-MM-DD
    end_date: str         # YYYY-MM-DD
    horizon_days: int = 90


# ── Helpers ────────────────────────────────────────────────────────────────────

def _get_run(run_id: str) -> dict:
    conn = get_conn()
    row = conn.execute("SELECT * FROM backtest_lab_runs WHERE id=?", (run_id,)).fetchone()
    conn.close()
    if not row:
        raise HTTPException(404, "Run not found")
    return dict(row)


def _row_to_dict(row) -> dict:
    d = dict(row)
    for field in ("assets", "context_snapshot", "ai_result", "outcome"):
        if d.get(field) and isinstance(d[field], str):
            try:
                d[field] = json.loads(d[field])
            except Exception:
                pass
    return d


# ── Endpoints ──────────────────────────────────────────────────────────────────

@router.post("/run")
async def create_run(req: RunRequest):
    """Build historical context + run AI analysis. Returns run with AI patterns."""
    from services.pattern_lab import build_historical_context, run_ai_backtest

    openai_key = get_config("openai_api_key") or ""
    if not openai_key:
        raise HTTPException(400, "OpenAI API key not configured")

    run_id = f"LAB_{uuid.uuid4().hex[:8].upper()}"
    now    = datetime.utcnow().isoformat()

    # Persist run in pending state
    conn = get_conn()
    conn.execute("""INSERT INTO backtest_lab_runs
        (id, preset_id, theme, analysis_date, horizon_days, assets, theme_hint, status, created_at)
        VALUES (?,?,?,?,?,?,?,'running',?)""", (
        run_id, req.preset_id, req.theme, req.analysis_date,
        req.horizon_days, json.dumps(req.assets), req.theme_hint, now,
    ))
    conn.commit()
    conn.close()

    try:
        # Step 1: historical context
        context = build_historical_context(req.analysis_date, req.assets)

        # Step 2: AI analysis
        ai_result = await run_ai_backtest(context, req.theme_hint, req.horizon_days, openai_key)

        # Persist results
        conn = get_conn()
        conn.execute("""UPDATE backtest_lab_runs SET
            context_snapshot=?, ai_result=?, status='done'
            WHERE id=?""", (
            json.dumps(context), json.dumps(ai_result), run_id,
        ))
        conn.commit()
        conn.close()

        return {
            "run_id":   run_id,
            "status":   "done",
            "context":  context,
            "ai_result": ai_result,
        }

    except Exception as e:
        conn = get_conn()
        conn.execute("UPDATE backtest_lab_runs SET status='error', error_msg=? WHERE id=?",
                     (str(e), run_id))
        conn.commit()
        conn.close()
        raise HTTPException(500, f"Backtest failed: {e}")


@router.post("/evaluate/{run_id}")
def evaluate_run(run_id: str):
    """Fetch actual prices at T+horizon and score each AI pattern."""
    from services.pattern_lab import evaluate_outcomes

    run = _get_run(run_id)
    if run["status"] not in ("done", "evaluated"):
        raise HTTPException(400, f"Run status is '{run['status']}', must be 'done' first")

    outcomes = evaluate_outcomes(run)

    conn = get_conn()
    conn.execute("""UPDATE backtest_lab_runs SET
        outcome=?, status='evaluated', evaluated_at=datetime('now')
        WHERE id=?""", (json.dumps(outcomes), run_id))
    conn.commit()
    conn.close()

    return {"run_id": run_id, "outcomes": outcomes}


@router.get("/runs")
def list_runs():
    conn = get_conn()
    rows = conn.execute("""SELECT id, preset_id, theme, analysis_date, horizon_days,
        assets, status, created_at, evaluated_at,
        outcome, ai_result
        FROM backtest_lab_runs ORDER BY created_at DESC LIMIT 100""").fetchall()
    conn.close()
    return [_row_to_dict(r) for r in rows]


@router.get("/runs/{run_id}")
def get_run(run_id: str):
    return _row_to_dict(_get_run(run_id))


@router.delete("/purge-all")
def purge_all_runs():
    """Delete all Pattern Lab runs."""
    conn = get_conn()
    conn.execute("DELETE FROM backtest_lab_runs")
    n = conn.total_changes
    conn.commit()
    conn.close()
    return {"deleted": n}


@router.delete("/runs/{run_id}")
def delete_run(run_id: str):
    conn = get_conn()
    conn.execute("DELETE FROM backtest_lab_runs WHERE id=?", (run_id,))
    conn.commit()
    conn.close()
    return {"deleted": run_id}


@router.post("/instrument-scan")
async def instrument_scan(req: InstrumentScanRequest):
    """Scan an instrument's historical price action to extract pattern instances."""
    from services.pattern_lab import run_instrument_scan

    openai_key = get_config("openai_api_key") or ""
    if not openai_key:
        raise HTTPException(400, "OpenAI API key not configured")

    run_id = f"LAB_INS_{uuid.uuid4().hex[:8].upper()}"
    now    = datetime.utcnow().isoformat()

    conn = get_conn()
    conn.execute("""INSERT INTO backtest_lab_runs
        (id, preset_id, theme, analysis_date, horizon_days, assets, theme_hint, status, created_at)
        VALUES (?,?,?,?,?,?,?,'running',?)""", (
        run_id,
        "instrument_scan",
        f"Instrument Scan: {req.instrument_name}",
        req.start_date,
        req.horizon_days,
        json.dumps([req.ticker]),
        json.dumps({"type": "instrument", "ticker": req.ticker,
                    "instrument_name": req.instrument_name,
                    "start_date": req.start_date, "end_date": req.end_date}),
        now,
    ))
    conn.commit()
    conn.close()

    try:
        ai_result = await run_instrument_scan(
            req.ticker, req.instrument_name,
            req.start_date, req.end_date,
            req.horizon_days, openai_key,
        )

        conn = get_conn()
        conn.execute("""UPDATE backtest_lab_runs SET
            ai_result=?, status='done'
            WHERE id=?""", (json.dumps(ai_result), run_id))
        conn.commit()
        conn.close()

        return {"run_id": run_id, "status": "done", "ai_result": ai_result}

    except Exception as e:
        conn = get_conn()
        conn.execute("UPDATE backtest_lab_runs SET status='error', error_msg=? WHERE id=?",
                     (str(e), run_id))
        conn.commit()
        conn.close()
        raise HTTPException(500, f"Instrument scan failed: {e}")


@router.post("/evaluate-instrument/{run_id}")
def evaluate_instrument_run(run_id: str):
    """Evaluate outcomes for an instrument scan (per-pattern dates)."""
    from services.pattern_lab import evaluate_instrument_outcomes

    run = _get_run(run_id)
    if run["status"] not in ("done", "evaluated"):
        raise HTTPException(400, f"Run status is '{run['status']}', must be 'done' first")

    outcomes = evaluate_instrument_outcomes(run)

    conn = get_conn()
    conn.execute("""UPDATE backtest_lab_runs SET
        outcome=?, status='evaluated', evaluated_at=datetime('now')
        WHERE id=?""", (json.dumps(outcomes), run_id))
    conn.commit()
    conn.close()

    return {"run_id": run_id, "outcomes": outcomes}


@router.post("/save-pattern")
def save_pattern_from_run(req: SavePatternRequest):
    """Promote one AI-suggested pattern (with its outcome) to the pattern library."""
    run = _get_run(req.run_id)

    ai_result = json.loads(run.get("ai_result") or "{}")
    patterns  = ai_result.get("patterns", [])
    if req.pattern_index >= len(patterns):
        raise HTTPException(400, "pattern_index out of range")

    pat = patterns[req.pattern_index]
    outcome_list: list = []
    if run.get("outcome"):
        try:
            outcome_list = json.loads(run["outcome"]) if isinstance(run["outcome"], str) else run["outcome"]
        except Exception:
            pass

    # Match outcome for this pattern
    outcome = next((o for o in outcome_list if o.get("pattern_name") == pat.get("name")), None)
    hit = bool(outcome.get("hit")) if outcome else None
    actual_move = outcome.get("actual_move_pct") if outcome else None

    pat_name = req.name or pat.get("name", "Unnamed Pattern")

    # Check if same name already exists → update reliability counters
    conn = get_conn()
    existing = conn.execute(
        "SELECT id, backtest_hits, backtest_runs_count FROM custom_patterns WHERE name=? AND source='backtested'",
        (pat_name,)
    ).fetchone()

    if existing:
        new_hits  = (existing["backtest_hits"] or 0) + (1 if hit else 0)
        new_runs  = (existing["backtest_runs_count"] or 0) + 1
        conn.execute("""UPDATE custom_patterns
            SET backtest_hits=?, backtest_runs_count=?, updated_at=datetime('now')
            WHERE id=?""", (new_hits, new_runs, existing["id"]))
        conn.commit()
        conn.close()
        return {"saved": existing["id"], "action": "updated", "backtest_hits": new_hits, "backtest_runs_count": new_runs}

    # New pattern
    new_id = f"P_LAB_{uuid.uuid4().hex[:6].upper()}"
    historical_instance = {
        "date":       run["analysis_date"],
        "horizon":    run["horizon_days"],
        "theme":      run["theme"],
        "hit":        hit,
        "actual_move_pct": actual_move,
    }

    conn.execute("""INSERT INTO custom_patterns (
        id, name, description, triggers, keywords, historical_instances,
        suggested_trades, asset_class, expected_move_pct, probability,
        horizon_days, source, category, signal_direction,
        backtest_hits, backtest_runs_count,
        is_active, taxonomy_path, updated_at
    ) VALUES (?,?,?,?,?,?,?,?,?,?,?,'backtested',?,?,?,?,1,'[]',datetime('now'))""", (
        new_id,
        pat_name,
        pat.get("description", ""),
        json.dumps([]),
        json.dumps([]),
        json.dumps([historical_instance]),
        json.dumps([{
            "underlying":         pat.get("underlying", ""),
            "strategy":           pat.get("strategy", ""),
            "expected_move_pct":  pat.get("expected_move_pct", 0),
            "asset_class":        req.asset_class,
        }]),
        req.asset_class or "indices",
        pat.get("expected_move_pct", 0),
        pat.get("confidence", 50) / 100,
        pat.get("horizon_days", run["horizon_days"]),
        req.category or pat.get("category", ""),
        req.signal_direction or pat.get("signal_direction", ""),
        1 if hit else 0,
        1,
    ))
    conn.commit()
    conn.close()

    return {"saved": new_id, "action": "created", "backtest_hits": 1 if hit else 0, "backtest_runs_count": 1}