AI Trading Charts: Annotations With Provenance, A Wording Check And A Person Who Publishes

"""Detect chart events from sample OHLC bars and describe them without advice.

The model may later polish the wording, but the events and every figure come from this code. The
check at the end refuses wording that predicts, recommends or targets a price. Python 3.14 standard
library only. Synthetic bars only. Not a trading signal.
"""
from __future__ import annotations

import re
import statistics

BARS = [  # (time, open, high, low, close, volume), synthetic
    ("09:00", 100.0, 100.6, 99.7, 100.2, 1200), ("09:05", 100.2, 100.5, 99.9, 100.1, 1100),
    ("09:10", 100.1, 100.4, 99.8, 100.3, 1000), ("09:15", 100.3, 100.6, 99.9, 100.0, 1150),
    ("09:20", 100.0, 100.5, 99.8, 100.4, 1050), ("09:25", 100.4, 101.9, 100.3, 101.7, 3900),
    ("09:30", 102.6, 102.9, 102.1, 102.4, 2100),
]
ADVICE = re.compile(r"\b(buy|sell|should|target|will (rise|fall)|expect|recommend|breakout likely)\b", re.I)


def events(bars: list[tuple[str, float, float, float, float, int]]) -> list[str]:
    out: list[str] = []
    for i in range(5, len(bars)):
        window = bars[i - 5:i]
        hi, lo = max(b[2] for b in window), min(b[3] for b in window)
        avg_vol = statistics.mean(b[5] for b in window)
        t, o, h, l, c, v = bars[i]
        if h > hi:
            out.append(f"At {t} the high of {h:.1f} was above the previous five-bar range of {lo:.1f} to {hi:.1f}.")
        if v > 2 * avg_vol:
            out.append(f"Volume at {t} was {v / avg_vol:.1f} times the five-bar average.")
        prev_close = bars[i - 1][4]
        if abs(o - prev_close) / prev_close > 0.005:
            out.append(f"The bar at {t} opened at {o:.1f}, {o - prev_close:+.1f} from the previous close.")
    return out


def wording_ok(text: str) -> bool:
    return ADVICE.search(text) is None


if __name__ == "__main__":
    for e in events(BARS):
        print("OK  " if wording_ok(e) else "BAD ", e)
    print("model draft check:", wording_ok("Price will rise after this breakout, consider buying."))

Python 3.14.4, standard library only. Run once as shown. Synthetic bars only. Not a trading signal.

"""Provenance and approval for AI-drafted chart annotations.

Anthropic's release notes (3 November 2026) say text from Claude Mythos 5, Claude Opus 4.7 and Claude
Sonnet 4.6 carries Anthropic's text watermark on listed platforms, and that on Sonnet 4.6 a request with a
non-default temperature, top_p or top_k might not carry it. This record keeps your own label anyway, flags
non-default sampling, and publishes only after a named approval. Python 3.14 standard library only.
"""
from __future__ import annotations

import hashlib
import json
from datetime import datetime, timezone

LOG: list[dict[str, object]] = []


def record(entry: dict[str, object]) -> str:
    prev = str(LOG[-1]["hash"]) if LOG else "0" * 64
    body = {**entry, "prev": prev, "at": datetime.now(timezone.utc).isoformat()}
    h = hashlib.sha256(json.dumps(body, sort_keys=True).encode()).hexdigest()
    LOG.append({**body, "hash": h})
    return h


def draft(text: str, model: str, sampling: dict[str, float]) -> dict[str, object]:
    notes = []
    if model == "claude-sonnet-4-6" and sampling:
        notes.append("non-default sampling: provider watermark may be absent, rely on our label")
    entry = {"text": text, "model": model, "sampling": sampling, "label": "AI-assisted description",
             "notes": notes, "status": "draft"}
    record({"event": "drafted", **entry})
    return entry


def publish(entry: dict[str, object], approver: str | None) -> str:
    if not approver:
        record({"event": "publish_refused", "text": entry["text"]})
        return "refused: needs a named approver"
    record({"event": "published", "text": entry["text"], "approver": approver, "label": entry["label"]})
    return f"published with label '{entry['label']}', approved by {approver}"


if __name__ == "__main__":
    a = draft("Volume at 09:25 was 3.6 times the five-bar average.", "claude-sonnet-4-6", {"temperature": 0.7})
    print("notes:", a["notes"])
    print(publish(a, None))
    print(publish(a, "desk.supervisor@example.co.uk"))
    for e in LOG:
        print(f"  {e['event']:<16} {str(e['hash'])[:12]}")

Python 3.14.4, standard library only. Run once as shown. Sample data only.