in indusindbank-tcs-sumsell bot i am getting dashes
2026-09-07 23:45
ASSISTANT (hermes, glm-5.3-flash)
2026-09-07 23:45
TOOL (hermes, glm-5.3-flash)
[Tool: skill_view]
{"success": true, "name": "ratiobot-pair-scanner", "description": "Use when working on the ratiobot pair-ratio scanner.", "tags": [], "related_skills": [], "content": "---\nname: ratiobot-pair-scanner\ndescription: Use when working on the ratiobot pair-ratio scanner.\n---\n\n# Ratiobot — Pair Ratio Scanner (studio.openalgo.theworkpc.com/ratiobot)\n\nPair-ratio scanner + two-leg futures signal builder. Lives inside bot-studio\n(Flask, port 5302). Reads pair data from the finratio chart server\n(127.0.0.1:5202), which already computes spread/sum series + indicators\n(vidya, sma, rsi, atr, macd, stoch, utbot) and daily 3-candle. The 15m\n3-candle is computed in the ratiobot backend from finratio candles (same\nformula as the finratio browser: 0.20*mean(i-2)+0.40*mean(i-1)+0.40*mean(i)).\n\n## Files\n- Backend: /home/ubuntu/bots/bot-studio/studio.py (routes appended before\n `if __name__`). Backup: studio.py.bak.20260907_ratiobot.\n- Template: /home/ubuntu/bots/bot-studio/templates/ratiobot.html\n- State: /home/ubuntu/bots/bot-studio/ratiobot_state.json\n- Service: bot-studio.service (restart after studio.py changes).\n\n## Routes\n- GET /ratiobot — the page\n- GET /api/ratiobot/symbols — finratio symbol list\n- GET /api/ratiobot/saved — list pairs saved in finratio (tcharts finratio)\n- POST /api/ratiobot/load — load a saved pair's factors (mult, kv, chartMode,\n interval, brick, bars, days, seriesMode, checks) to auto-fill the form\n- POST /api/ratiobot/scan — evaluates conditions against finratio snapshots\n- POST /api/ratiobot/track — per-candle tracking table (candle #, date/time,\n 15m 3-Candle, UT Bot, ratio) + live futures LTP + signal trigger history\n- POST /api/ratiobot/legs — resolves the two futures legs\n- POST /api/ratiobot/place — places the futures orders (auto mode)\n\n## Tracking table (POST /api/ratiobot/track)\nReturns per-5m-candle rows: candle #, date, time, 15m 3-Candle, UT Bot, ratio\n(pair series). Plus live futures LTP (via broker /api/v1/quotes — note PLURAL,\n/quote returns SPA HTML) and signal trigger history (when last triggered, how\nmany candles back, stayed how long, start/end ts, price at trigger).\n- 15m 3-Candle alignment: 5m ts and 15m ts are on DIFFERENT boundaries. Map each\n 5m ts to the containing 15m candle (latest 15m boundary <= 5m ts), not exact match.\n- Early rows show '—' for 15m 3-Candle when outside the 5-day 15m candle window.\n- Broker quote endpoint is /api/v1/quotes (plural), NOT /api/v1/quote.\n\n## Modes (pair construction)\n- spread: pair = A/B. pair-buy = buy A + sell B; pair-sell = sell A + buy B\n- sum: pair = A+B. pair-buy = buy A + buy B; pair-sell = sell A + sell B\n- direction field (both | buy-only | sell-only) filters which legs fire:\n buy-only keeps only BUY legs, sell-only keeps only SELL legs. Applied in\n _build_legs AFTER the mode builds both legs.\n\n## Daemon (server-side runner)\n- ratiobot-daemon.service runs /home/ubuntu/bots/bot-studio/ratiobot_dae
... [9794 chars total, truncated]
2026-09-07 23:45
ASSISTANT (hermes, glm-5.3-flash)
2026-09-07 23:45
TOOL (hermes, glm-5.3-flash)
[Tool: skill_view]
{"success": true, "name": "trading-hive-access", "description": "Use when connecting to the trading VPS or laptop.", "tags": [], "related_skills": [], "content": "---\nname: trading-hive-access\ndescription: Use when connecting to the trading VPS or laptop.\n---\n\n# Trading Hive Access\n\n## Machines\n- **VPS** (broker egress anchor): host alias `trading` in `~/.ssh/config`\n - HostName 144.217.12.244, User ubuntu, IdentityFile ~/.ssh/id_ed25519\n - Tailscale 100.115.98.47 (vps-2c5ca245)\n - Runs: OpenAlgo broker instances (flattrade, kotak, shoonya), nginx public front door\n- **Laptop** harsheen-Precision-3541: Tailscale 100.93.26.64, wifi 192.168.1.18\n - Runs: the full trading stack (bots, chart-data-api, tcharts, ratio, finratio,\n live-quote-filler, positions-dashboard, rust-screener, rust-studio, bot-studio)\n\n## SSH access\n- Laptop → VPS: `ssh trading` (key auth, id_ed25519 installed)\n- VPS user: ubuntu\n\n## Skills storage\n- Trading skills live in `~/.hermes/skills/trading/` on BOTH machines (synced from VPS).\n- Backed up to Turso DB `skills-hermes-hnsi` (libsql://skills-hermes-hnsi.aws-ap-south-1.turso.io),\n table `hermes_skills(skill_path PK, content, sha256, updated_at)`, ~1289 rows.\n Credentials: `TURSO_SKILLS_DB_URL` / `TURSO_SKILLS_DB_AUTH_TOKEN` in `~/.gemini/.env` on the VPS.\n- Chat archive Turso DB: `chat-archive` (libsql://chat-archive-hnsi.aws-ap-south-1.turso.io),\n creds `TURSO_CHAT_DB_URL` / `TURSO_CHAT_DB_AUTH_TOKEN` in same .env.\n\n## Broker OpenAlgo instances (on laptop, unix sockets)\n- Root: /var/python/openalgo-flask/<broker>-openalgo.theworkpc.com-<broker>/openalgo/\n- Socket: <instance>/openalgo.sock\n- API keys: /var/www/openalgo-chart/api/broker_config.py (BROKER_API_KEYS dict)\n- WS ports: shoonya=8765, flattrade=8766, kotak=8767\n- ZMQ ports: shoonya=5555, flattrade=5556, kotak=5557\n\n## Data pipeline\n- Values DBs (single source of truth): /var/www/openalgo-chart/api/dbs/<sym>_values.db\n (tables: renko_bricks, indicator_snapshots, daily_values, xover_events)\n- Chart API: http://127.0.0.1:5050\n- Tradebot: /home/ubuntu/bots/tradebot/ (bot.py, symbols.yaml, state/, logs/)\n\n## Broker tokens & migration (READ THIS FIRST — do not re-investigate)\n- **`trading/broker-token-migration.md`** — the full architecture, the migration gap that\n broke flattrade/kotak, the token store (24h, per-machine), the token bridges, how to refresh\n each broker's token, and the health-check script. Load it before touching broker tokens.\n- All 3 token bridges (`token-bridge-<broker>.service`) are ACTIVE + ENABLED at boot.\n- All 3 broker tokens are stored in each instance's `db/openalgo.db` `auth` table (encrypted\n with that instance's own key). Tokens valid ~24h, cleared ~3 AM IST.\n- Kotak login is fully automatic (`kotak_login.py`); shoonya/flattrade need OAuth browser login.\n- Health check: `/usr/local/bin/broker_token_health.py <broker>` (run with broker's own venv, as www-data).\n
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The bot exists — INDUSINDBK-TCS-sum-sell (sum mode, sell-only, armed, auto). Let me hit the track API to see where the dashes are.
2026-09-07 23:46
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "keys: ['message', 'status']\nrows: 0", "exit_code": 0, "error": null, "approval": "Command was flagged (Security scan — [HIGH] Pipe to interpreter: curl | python3: Command pipes output from 'curl' directly to interpreter 'python3'. Downloaded content will be executed without inspection.\n Safer: run `tirith check --suggest -- <command>`; Tirith emits a typed capsule command only when it can prove the URL, interpreter, argv, and stdin semantics. Otherwise download into a private location (or use `vet <url>`, https://getvet.sh) and review the exact bytes before execution.; [HIGH] Nested executable body could not be resolved: The shell will execute a grouped, encoded, or dynamically selected value, but Tirith cannot prove the complete executable body. The command is blocked instead of trusting its benign-looking outer leader.; [HIGH] nested command analysis was incomplete: A destructive command may be hidden beyond Tirith's bounded nested-shell depth, lexical-candidate, input, or retained-body budget.; script execution via -e/-c flag) and auto-approved by smart approval."}
2026-09-07 23:46
ASSISTANT (hermes, glm-5.3-flash)
2026-09-07 23:46
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "1718:@app.route(\"/api/ratiobot/track\", methods=[\"POST\"])\n1719-def api_ratiobot_track():\n1720- \"\"\"Per-candle tracking table: candle #, date/time, 15m 3-Candle, UT Bot,\n1721- ratio (pair series), plus live futures LTP. Also signal trigger history.\"\"\"\n1722- data = request.get_json(force=True) or {}\n1723- a = (data.get(\"a\") or \"\").strip().upper()\n1724- b = (data.get(\"b\") or \"\").strip().upper()\n1725- if not a or not b:\n1726- return jsonify({\"status\": \"error\", \"message\": \"a and b required\"}), 400\n1727- pair = f\"{a}-{b}\"\n1728- mode = data.get(\"mode\", \"spread\")\n1729- series_mode = \"sum\" if mode == \"sum\" else \"spread\"\n1730- mult = float(data.get(\"mult\", 100))\n1731- interval = data.get(\"interval\", \"5m\")\n1732- kv = float(data.get(\"kv\", 10))\n1733- broker = data.get(\"broker\", \"kotak\")\n1734- conditions = data.get(\"conditions\", [])\n1735-\n1736- # Per-candle series from finratio snapshots (5m base)\n1737- snap = _finratio_get(f\"/api/snapshots/{pair}\",\n1738- {\"series\": 1, \"limit\": 300, \"mult\": mult,\n1739- \"mode\": series_mode, \"keyvalue\": kv, \"interval\": \"5m\"})\n1740- if snap.get(\"status\") != \"success\":\n1741- return jsonify({\"status\": \"error\", \"message\": snap.get(\"message\", \"snapshots failed\")}), 502\n1742- series = snap.get(\"series\") or {}\n1743- price_s = series.get(\"price\", [])\n1744- utbot_s = series.get(\"utbot\", [])\n1745-\n1746- # 15m 3-candle series — fetch ENOUGH days to cover the 200-candle window.\n1747- # The price series spans (200 5m candles ≈ up to 10+ trading days), so days=5\n1748- # left older rows without a 15m3c value (dashes). Use the window span.\n1749- days_span = 1\n1750- if len(price_s) > 1:\n1751- try:\n1752- t0 = time.mktime(time.strptime(price_s[0][\"ts\"], \"%Y-%m-%d %H:%M:%S\"))\n1753- t1 = time.mktime(time.strptime(price_s[-1][\"ts\"], \"%Y-%m-%d %H:%M:%S\"))\n1754- days_span = max(2, int((t1 - t0) / 86400) + 1)\n1755- except Exception:\n1756- days_span = max(int(data.get(\"days\", 10)), 10)\n1757- cd = _finratio_get(f\"/api/candles/{pair}\",\n1758- {\"interval\": \"15m\", \"days\": days_span, \"mult\": mult, \"mode\": series_mode})\n1759- candles = cd.get(\"candles\", []) if cd.get(\"status\") == \"success\" else []\n1760- line15 = _compute_15m3candle(candles)\n1761- # Map each 5m ts to the containing 15m candle (latest 15m boundary <= 5m ts)\n1762- def _ts_to_epoch(ts):\n1763- try:\n1764- return time.mktime(time.strptime(ts, \"%Y-%m-%d %H:%M:%S\"))\n1765- except Exception:\n1766- return 0\n1767- line15_epochs = [(_ts_to_epoch(p[\"ts\"]), p[\"value\"]) for p in line15]\n1768- def _c15m3_for(ts):\n1769- e = _ts_to_epoch(ts)
... [3964 chars total, truncated]
2026-09-07 23:46
ASSISTANT (hermes, glm-5.3-flash)
2026-09-07 23:46
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "# Build per-candle rows aligned by ts (use price series as the anchor)\n # Precompute per-candle signal state from the CONFIGURED conditions,\n # respecting each condition's buy/sell direction.\n cond_state = {} # ts -> \"buy\" | \"sell\" | \"neutral\"\n for c in conditions:\n op = c.get(\"op\")\n track = c.get(\"trackable\")\n target = c.get(\"target\")\n sig = c.get(\"signal\", \"buy\")\n if op not in (\"cross_above\", \"cross_below\"):\n continue\n sa = _get_series(track, snap, pair, mult, series_mode)\n if isinstance(target, str) and target in TRACKABLES:\n sb = _get_series(target, snap, pair, mult, series_mode)\n else:\n sb = [{\"ts\": p[\"ts\"], \"value\": float(target)} for p in sa]\n sb_map = {p[\"ts\"]: p[\"value\"] for p in sb}\n for pa in sa:\n ts = pa[\"ts\"]\n a_val = pa[\"value\"]\n b_val = sb_map.get(ts)\n if a_val is None or b_val is None:\n continue\n if op == \"cross_above\":\n state = sig if a_val > b_val else \"neutral\"\n else:\n state = sig if a_val < b_val else \"neutral\"\n # Only overwrite neutral with a real signal (first condition wins)\n if cond_state.get(ts, \"neutral\") == \"neutral\" and state != \"neutral\":\n cond_state[ts] = state\n\n rows = []\n # ── Continuous time grid ────────────────────────────────────────────\n # Full sweep of interval slots per trading day (5m -> 09:15..15:40,\n # 15m -> 09:15..15:30), NO gaps: renko bricks can skip minutes/hours,\n # so indicator values carry forward until the next brick prints.\n try:\n iv_min = int(str(interval).replace(\"m\", \"\"))\n except Exception:\n iv_min = 5\n price_map = {p[\"ts\"]: p[\"value\"] for p in price_s}\n utbot_map = {u[\"ts\"]: u[\"value\"] for u in utbot_s}\n # Build value maps for every trackable used in conditions (incl. numeric\n # targets). Signals are recomputed per slot from these maps + carry, so\n # exits are never delayed on empty (no-brick) slots.\n cond_series = {} # key -> {ts: value}\n for c in conditions:\n for role in (\"trackable\", \"target\"):\n key = c.get(role)\n if isinstance(key, str) and key in TRACKABLES and key not in cond_series:\n s = _get_series(key, snap, pair, mult, series_mode)\n cond_series[key] = {p[\"ts\"]: p[\"value\"] for p in s if p[\"value\"] is not None}\n # trading dates seen in the data (price series + 15m line)\n dates = sorted({p[\"ts\"][:10] for p in price_s} | {l[\"ts\"][:10] for l in line15})\n START = 9 * 60 + 15 # 09:15\n END = 15 * 60 + 45 # last slot must end by 15:45\n grid = []\n for d in dates:\n t = START\n while t < END:\n grid.append(f\"{d} {t
... [4051 chars total, truncated]
2026-09-07 23:46
ASSISTANT (hermes, glm-5.3-flash)
2026-09-07 23:46
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "if op not in (\"cross_above\", \"cross_below\"):\n continue\n cval = vals.get(c.get(\"trackable\"))\n tkey = c.get(\"target\")\n if isinstance(tkey, str) and tkey in TRACKABLES:\n tval = vals.get(tkey)\n else:\n try:\n tval = float(tkey)\n except (TypeError, ValueError):\n tval = None\n if cval is None or tval is None:\n continue\n if op == \"cross_above\":\n state = c.get(\"signal\", \"buy\") if cval > tval else \"neutral\"\n else:\n state = c.get(\"signal\", \"buy\") if cval < tval else \"neutral\"\n if sig == \"neutral\" and state != \"neutral\":\n sig = state\n carry = {\"ratio\": ratio, \"utbot\": ub, \"c15m3\": c15,\n \"cond_vals\": {k: v for k, v in vals.items()\n if k not in (\"ratio\", \"utbot\", \"c15m3\")}}\n transition = (prev_signal is not None and sig != prev_signal)\n rows.append({\n \"candle\": i + 1,\n \"ts\": ts,\n \"time\": ts[11:16] if len(ts) > 16 else ts,\n \"date\": ts[:10],\n \"interval\": iv_min,\n \"ratio\": ratio,\n \"utbot\": ub,\n \"c15m3\": c15,\n \"signal\": sig,\n \"transition\": transition,\n })\n prev_signal = sig\n\n # Live futures LTP (current, not per-candle)\n fa = _resolve_futures(a, broker)\n fb = _resolve_futures(b, broker)\n live = {}\n for sym, fut in ((\"A\", fa), (\"B\", fb)):\n if fut and fut.get(\"symbol\"):\n q = _finratio_get(f\"/api/candles/{fut['symbol']}?interval=5m&days=1\")\n # fallback: broker quote via direct call\n live[sym] = {\"symbol\": fut.get(\"symbol\"), \"ltp\": None}\n # Try broker quotes for live LTP\n try:\n sys.path.insert(0, \"/home/ubuntu/bots/tradebot\")\n from config import BROKER_URLS, BROKER_API_KEYS\n base = BROKER_URLS.get(broker)\n api_key = BROKER_API_KEYS.get(broker)\n for sym, fut in ((\"A\", fa), (\"B\", fb)):\n if fut and fut.get(\"symbol\") and base and api_key:\n r = _requests.post(f\"{base}/api/v1/quotes\",\n json={\"apikey\": api_key, \"symbol\": fut[\"symbol\"],\n \"exchange\": \"NFO\"}, timeout=8)\n d = r.json()\n live[sym][\"ltp\"] = d.get(\"data\", {}).get(\"ltp\") if d.get(\"status\") == \"success\" else None\n except Exception:\n pass\n\n # Signal trigger history: walk the price series, find when the condition\n # last turned true, how many candles it stayed, when it ended.\n history = []\n for c in conditions:\n op = c.get(\"op\")\n track =
... [3458 chars total, truncated]
2026-09-07 23:46
ASSISTANT (hermes, glm-5.3-flash)
The endpoint looks right. Let me call it with the bot's actual config and inspect the returned rows — plus check what the finratio snapshots return for this pair in sum mode.
The API returns 200 rows with values at the tail. Now let me check the earlier rows and how the cockpit's scan-all builds its track body — that's where a mismatch could show dashes.
175/200 rows have `ratio: None` (utbot/c15m3 carry fine). Let me see where ratio starts and what the finratio sum-series actually returns.
2026-09-07 23:46
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "first row WITH ratio: ('2026-09-07 13:40:00', 121000000.0)\nfirst row AT ALL: 2026-09-03 12:05:00\n('2026-09-03', True) 44\n('2026-09-04', True) 78\n('2026-09-07', False) 25\n('2026-09-07', True) 53\nstatus: success | msg: None\natr points: 300 | first ts: 2026-02-01 07:30:00 | last ts: 2026-09-07 13:40:00\nmacd points: 300 | first ts: 2026-02-01 07:30:00 | last ts: 2026-09-07 13:40:00\nmacd_hist points: 300 | first ts: 2026-02-01 07:30:00 | last ts: 2026-09-07 13:40:00\nmacd_signal points: 300 | first ts: 2026-02-01 07:30:00 | last ts: 2026-09-07 13:40:00\nprice points: 300 | first ts: 2026-02-01 07:30:00 | last ts: 2026-09-07 13:40:00\nrsi points: 300 | first ts: 2026-02-01 07:30:00 | last ts: 2026-09-07 13:40:00\nsma20 points: 300 | first ts: 2026-02-01 07:30:00 | last ts: 2026-09-07 13:40:00\nsma50 points: 287 | first ts: 2026-02-04 03:45:00 | last ts: 2026-09-07 13:40:00\nstoch_d points: 300 | first ts: 2026-02-01 07:30:00 | last ts: 2026-09-07 13:40:00\nstoch_k points: 300 | first ts: 2026-02-01 07:30:00 | last ts: 2026-09-07 13:40:00\nutbot points: 12745 | first ts: 2026-01-01 04:55:00 | last ts: 2026-09-07 15:30:00\nvidya points: 300 | first ts: 2026-02-01 07:30:00 | last ts: 2026-09-07 13:40:00", "exit_code": 0, "error": null, "approval": "Command was flagged (script execution via heredoc) and auto-approved by smart approval."}
2026-09-07 23:46
ASSISTANT (hermes, glm-5.3-flash)
The sum-mode price series is sparse (300 points spanning Feb→Sep, last point 13:40 today) while utbot is dense. Let me check the spread-mode series for comparison and how scan-all builds the track body.
2026-09-07 23:47
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "spread price points: 300 | first: 2026-08-07 09:20:00 | last: 2026-09-07 15:10:00\nspread utbot points: 12745 | first: 2026-01-01 04:55:00 | last: 2026-09-07 15:30:00\n \"b\": b,\n \"mode\": data.get(\"mode\", \"spread\"),\n \"direction\": data.get(\"direction\", \"both\"),\n \"broker\": data.get(\"broker\", \"kotak\"),\n \"signal_auto\": data.get(\"exec\", \"signal\"),\n \"conditions\": data.get(\"conditions\", []),\n \"pair_entry\": data.get(\"pair_entry\", prev.get(\"pair_entry\", {})),\n # preserve armed state on overwrite unless explicitly given\n \"armed\": bool(data.get(\"armed\", prev.get(\"armed\", False))),\n }\n _save_ratiobot_state(state)\n return jsonify({\"status\": \"success\", \"name\": name, \"saved\": True})\n\n\n@app.route(\"/api/ratiobot/bots/scan-all\", methods=[\"POST\"])\ndef api_ratiobot_bots_scan_all():\n \"\"\"One call for the cockpit: for every saved bot, return its config,\n scan results, and tracking rows. Browser only renders.\"\"\"\n state = _load_ratiobot_state()\n out = {}\n for name, cfg in state.items():\n pe = cfg.get(\"pair_entry\", {})\n mult = pe.get(\"mult\", cfg.get(\"mult\", 100))\n kv = pe.get(\"kv\", cfg.get(\"kv\", 10))\n interval = pe.get(\"interval\", cfg.get(\"interval\", \"5m\"))\n broker = cfg.get(\"broker\", \"kotak\")\n body = {\n \"a\": cfg.get(\"a\"),\n \"b\": cfg.get(\"b\"),\n \"mode\": cfg.get(\"mode\", \"spread\"),\n \"mult\": float(mult) if mult is not None else 100,\n \"kv\": float(kv) if kv is not None else 10,\n \"interval\": interval,\n \"conditions\": cfg.get(\"conditions\", []),\n }\n entry = {\n \"cfg\": {\n \"name\": name,\n \"a\": cfg.get(\"a\"), \"b\": cfg.get(\"b\"),\n \"mode\": cfg.get(\"mode\", \"spread\"),\n \"direction\": cfg.get(\"direction\", \"both\"),\n \"broker\": broker,\n \"exec\": cfg.get(\"signal_auto\", \"signal\"),\n \"armed\": bool(cfg.get(\"armed\", False)),\n \"conditions\": cfg.get(\"conditions\", []),\n \"pair_entry\": pe,\n },\n \"scan\": None,\n \"track\": None,\n }\n # scan\n try:\n with app.test_request_context(\"/api/ratiobot/scan\", method=\"POST\",\n json=body):\n resp = api_ratiobot_scan()\n entry[\"scan\"] = resp.get_json(silent=True) if hasattr(resp, \"get_json\") else resp\n except Exception as e:\n entry[\"scan\"] = {\"status\": \"error\", \"message\": str(e)}\n # track (adds broker for live LTP)\n try:\n tbody = dict(body)\n tbody[\"broker\"] = broker\n with app.tes
... [3195 chars total, truncated]
2026-09-07 23:47
ASSISTANT (hermes, glm-5.3-flash)
Spread-mode price is dense (Aug 7 → today); sum-mode is sparse (300 pts over 7 months, ~2/day) — the sum series barely prints bricks, and in the 200-slot window only one sum brick lands (13:40 today), so ratio shows as dash on earlier rows until carry kicks in. Let me check what brick the saved finratio pair uses and whether the snapshots endpoint honors it.
2026-09-07 23:47
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "{\n \"message\": \"name required\",\n \"status\": \"error\"\n}", "exit_code": 0, "error": null, "approval": "Command was flagged (script execution via heredoc) and auto-approved by smart approval."}
2026-09-07 23:47
ASSISTANT (hermes, glm-5.3-flash)
2026-09-07 23:47
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "1582: d = _finratio_get(\"/api/saved\")\n1593: d = _finratio_get(\"/api/saved\")\nindusindbk25aug261000ce_5min.db\nindusindbk25aug261000pe_5min.db\nindusindbk25aug261010ce_5min.db\nindusindbk25aug261010pe_5min.db\nindusindbk25aug261020ce_5min.db\nindusindbk25aug261020pe_5min.db\nindusindbk25aug261030ce_5min.db\nindusindbk25aug261030pe_5min.db\nindusindbk28jul26fut_daily_vidya.db\nindusindbk29sep261000ce_5min.db\nindusindbk29sep261000pe_5min.db\nindusindbk29sep261010ce_5min.db\nindusindbk29sep261010pe_5min.db\nindusindbk29sep26990ce_5min.db\nindusindbk29sep26990pe_5min.db\nindusindbk_5min.db\nindusindbk_5min_nfo_backup.db\nindusindbk_daily_vidya.db\nindusindbk_values.db", "exit_code": 0, "error": null}
[Tool: terminal]
{"output": "Cargo.lock\nCargo.toml\ndbs\nnginx\nrefresh_lots.py\nsaved_pairs.json\nsrc\nstatic\nsymbols.yaml\ntarget\n chart-data-api.service loaded active running Chart Data API (Flask/Gunicorn)\n finratio.service loaded active running FINRATIO Monetary Pair-Ratio Chart Server (port 5202)\n ratio.service loaded active running Ratio Pair-Chart Server (port 5201)\n tcharts.service loaded active running TCharts Rust Server (port 5101)", "exit_code": 0, "error": null}
Found it — the saved finratio pair uses mult=0.001, kv=5, but the ratiobot track call used mult=100, kv=10 (defaults). Let me verify that the correct mult gives a dense sum series.
Sum series is still sparse even with the right mult/kv — but the utbot series is dense. Let me look at the actual sum price points to understand what the series is.
Got it — I have the diagnosis; finishing the fix now. Quick check of what the finratio snapshots endpoint accepts:
2026-09-07 23:50
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "887:CREATE TABLE IF NOT EXISTS indicator_snapshots (\n928:CREATE INDEX IF NOT EXISTS idx_snap_interval ON indicator_snapshots(interval);\n1087: tx.execute(\"DELETE FROM indicator_snapshots WHERE interval = ?\", params![interval]).map_err(|e| e.to_string())?;\n1100: // ── Indicator snapshots on the renko bricks ──\n1144: \"SELECT MAX(time) FROM indicator_snapshots WHERE interval = ?\",\n1149: \"INSERT OR REPLACE INTO indicator_snapshots (interval, time, ts, price, vidya, sma20, sma50, rsi, atr, macd, macd_signal, macd_hist, stoch_k, stoch_d, computed_at) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)\"\n1889:async fn api_snapshots(axum::extract::Path(symbol): axum::extract::Path<String>, axum::extract::Query(params): axum::extract::Query<HashMap<String, String>>) -> (StatusCode, Json<Value>) {\n1902: \"SELECT time, ts, price, vidya, sma20, sma50, rsi, atr, macd, macd_signal, macd_hist, stoch_k, stoch_d, computed_at FROM indicator_snapshots WHERE interval = ? ORDER BY time DESC\",\n1932: \"SELECT time, ts, price, vidya, sma20, sma50, rsi, atr, macd, macd_signal, macd_hist, stoch_k, stoch_d FROM indicator_snapshots WHERE interval = ? ORDER BY time DESC LIMIT ?\"\n2160: \"SELECT time, ts, price, vidya, sma20, sma50, rsi, atr, macd, macd_signal, macd_hist, stoch_k, stoch_d, computed_at FROM indicator_snapshots WHERE interval = ? ORDER BY time DESC\",\n253: .query_row(\"SELECT value FROM meta WHERE key = 'brick_size'\", [], |r| r.get(0))\n1086: tx.execute(\"DELETE FROM renko_bricks WHERE interval = ?\", params![interval]).map_err(|e| e.to_string())?;\n1095: stmt.execute(params![interval, b.brick_index, b.ts, b.open, b.high, b.low, b.close, b.direction])\n1221: params![interval, bricks[i].ts, direction, sma2, r4(lv), r2(closes[k]), r2(bricks[i].close), &now]\n1647:async fn api_bricks(axum::extract::Path(symbol): axum::extract::Path<String>, axum::extract::Query(params): axum::extract::Query<HashMap<String, String>>) -> (StatusCode, Json<Value>) {\n1670: if let Some(pct_str) = params.get(\"brick_pct\") {\n1730: // If brick_size param is given and differs from default, recompute on the fly\n1731: if let Some(bs_str) = params.get(\"brick_size\") {\n2271: let r: i64 = c.query_row(\"SELECT COUNT(*) FROM renko_bricks WHERE interval='5m'\", [], |x| x.get(0)).unwrap_or(0);\n2272: let l: String = c.query_row(\"SELECT COALESCE(MAX(ts),'') FROM renko_bricks WHERE interval='5m'\", [], |x| x.get(0)).unwrap_or_default();", "exit_code": 0, "error": null}
[Tool: terminal]
{"output": "async fn api_snapshots(axum::extract::Path(symbol): axum::extract::Path<String>, axum::extract::Query(params): axum::extract::Query<HashMap<String, String>>) -> (StatusCode, Json<Value>) {\n let interval = norm_interval(params.get(\"interval\").map(|s| s.as_str()).unwrap_or(\"5m\"));\n let m = pair_mult(&symbol, ¶ms);\n let mode = PairMode::from_param(params.get(\"mode\"));\n // UT Bot \"Key Value\" multiplier (Pine `a`): default 10. Lower = tighter stop.\n let kv: f64 = params.get(\"keyvalue\").and_then(|s| s.parse().ok()).unwrap_or(10.0);\n ensure_fresh_mode(&symbol, mode).await;\n let conn = match open_computed_mode(&symbol, mode) {\n Some(c) => c,\n None => return (StatusCode::NOT_FOUND, Json(json!({\"status\":\"error\",\"message\":\"computed DB not found\"}))),\n };\n // Latest snapshot\n let latest: Option<Value> = conn.query_row(\n \"SELECT time, ts, price, vidya, sma20, sma50, rsi, atr, macd, macd_signal, macd_hist, stoch_k, stoch_d, computed_at FROM indicator_snapshots WHERE interval = ? ORDER BY time DESC\",\n params![interval], |r| Ok(json!({\n \"time\": r.get::<_, i64>(0)?,\n \"ts\": r.get::<_, String>(1)?,\n \"price\": r.get::<_, Option<f64>>(2)?,\n \"vidya\": r.get::<_, Option<f64>>(3)?,\n \"sma20\": r.get::<_, Option<f64>>(4)?,\n \"sma50\": r.get::<_, Option<f64>>(5)?,\n \"rsi\": r.get::<_, Option<f64>>(6)?,\n \"atr\": r.get::<_, Option<f64>>(7)?,\n \"macd\": r.get::<_, Option<f64>>(8)?,\n \"macd_signal\": r.get::<_, Option<f64>>(9)?,\n \"macd_hist\": r.get::<_, Option<f64>>(10)?,\n \"stoch_k\": r.get::<_, Option<f64>>(11)?,\n \"stoch_d\": r.get::<_, Option<f64>>(12)?,\n \"computed_at\": r.get::<_, String>(13)?,\n }))\n ).ok();\n\n let want_series = params.get(\"series\").map(|s| s == \"1\").unwrap_or(false);\n let mut resp = json!({\n \"status\": \"success\",\n \"symbol\": symbol.to_uppercase(),\n \"interval\": interval,\n \"latest\": latest,\n });\n\n if want_series {\n let limit: i64 = params.get(\"limit\").and_then(|s| s.parse().ok()).unwrap_or(100000);\n let mut stmt = match conn.prepare(\n \"SELECT time, ts, price, vidya, sma20, sma50, rsi, atr, macd, macd_signal, macd_hist, stoch_k, stoch_d FROM indicator_snapshots WHERE interval = ? ORDER BY time DESC LIMIT ?\"\n115:fn computed_db_path(sym: &str, mode: PairMode) -> String {\n119: return pair_computed_db_path_mode(&a, &b, mode);\n121: format!(\"{}/{}_computed.db\", dir, safe_name(sym))\n126:fn pair_computed_db_path_mode(a: &str, b: &str, mode: PairMode) -> String {\n129: format!(\"{}/{}_{}_{}_computed.db\", dir, safe_name(a), safe_name(b), mode.tag())\n243:fn pair_brick_size(comp_db: &str, latest_close: f64) -> f64 {\n283: .strip_suf
... [3251 chars total, truncated]
2026-09-07 23:50
ASSISTANT (hermes, glm-5.3-flash)
The finratio snapshots serve from `indusindbk_tcs_sum_computed.db` — renko bricks on the sum. The sum moves slowly (~0.083% brick), so it prints roughly one brick every few days. In your 200-slot window the only sum brick is 09-07 13:40 — everything before that has no ratio to carry, because the track code starts carry-forward **empty at the window start** instead of seeding it with the last brick *before* the window. That's the bug. Fixing now:
[Tool: patch]
{"success": true, "diff": "--- a//tmp/studio_edit.py\n+++ b//tmp/studio_edit.py\n@@ -1839,6 +1839,26 @@\n t += iv_min\n grid = grid[-200:] # most recent 200 slots\n carry = {}\n+ # Seed carry with the LAST known values BEFORE the grid window starts, so\n+ # slow pairs (sum renko bricks can be days apart) don't show dashes on\n+ # every slot until the next brick prints inside the window.\n+ seed_maps = {\"ratio\": price_map, \"utbot\": utbot_map}\n+ for k, mp in seed_maps.items():\n+ prev_v = None\n+ for ts in grid:\n+ if ts in mp:\n+ prev_v = mp[ts]\n+ break\n+ if prev_v is not None:\n+ carry[k] = prev_v\n+ for k, mp in cond_series.items():\n+ prev_v = None\n+ for ts in grid:\n+ if ts in mp:\n+ prev_v = mp[ts]\n+ break\n+ if prev_v is not None:\n+ carry.setdefault(\"cond_vals\", {})[k] = prev_v\n prev_signal = None\n for i, ts in enumerate(grid):\n # data at this slot? else carry the last known values forward\n", "files_modified": ["/tmp/studio_edit.py"], "lint": {"status": "ok", "output": ""}, "resolved_path": "/tmp/studio_edit.py"}
2026-09-07 23:50
ASSISTANT (hermes, glm-5.3-flash)
The seed loop needs to find the last value *before* the window, not the first inside it — let me correct that:
2026-09-07 23:51
TOOL (hermes, glm-5.3-flash)
[Tool: patch]
{"success": true, "diff": "--- a//tmp/studio_edit.py\n+++ b//tmp/studio_edit.py\n@@ -1841,24 +1841,30 @@\n carry = {}\n # Seed carry with the LAST known values BEFORE the grid window starts, so\n # slow pairs (sum renko bricks can be days apart) don't show dashes on\n- # every slot until the next brick prints inside the window.\n- seed_maps = {\"ratio\": price_map, \"utbot\": utbot_map}\n- for k, mp in seed_maps.items():\n- prev_v = None\n+ # every slot until the next brick prints inside the window. Series come\n+ # back DESC from SQL, so the first point with ts < grid[0] is the most\n+ # recent one before the window.\n+ window_start = grid[0] if grid else None\n+ def _seed(mp):\n+ if not window_start:\n+ return None\n+ for ts, v in mp.items(): # DESC order\n+ if ts < window_start and v is not None:\n+ return v\n+ # fall back: first value inside the window\n for ts in grid:\n- if ts in mp:\n- prev_v = mp[ts]\n- break\n- if prev_v is not None:\n- carry[k] = prev_v\n+ if ts in mp and mp[ts] is not None:\n+ return mp[ts]\n+ return None\n+ for k in (\"ratio\", \"utbot\"):\n+ mp = {\"ratio\": price_map, \"utbot\": utbot_map}[k]\n+ v = _seed(mp)\n+ if v is not None:\n+ carry[k] = v\n for k, mp in cond_series.items():\n- prev_v = None\n- for ts in grid:\n- if ts in mp:\n- prev_v = mp[ts]\n- break\n- if prev_v is not None:\n- carry.setdefault(\"cond_vals\", {})[k] = prev_v\n+ v = _seed(mp)\n+ if v is not None:\n+ carry.setdefault(\"cond_vals\", {})[k] = v\n prev_signal = None\n for i, ts in enumerate(grid):\n # data at this slot? else carry the last known values forward\n", "files_modified": ["/tmp/studio_edit.py"], "lint": {"status": "ok", "output": ""}, "resolved_path": "/tmp/studio_edit.py"}
2026-09-07 23:51
ASSISTANT (hermes, glm-5.3-flash)
One correction — the series arrive ascending, not DESC; make the seed order-agnostic:
2026-09-07 23:51
TOOL (hermes, glm-5.3-flash)
[Tool: patch]
{"success": true, "diff": "--- a//tmp/studio_edit.py\n+++ b//tmp/studio_edit.py\n@@ -1841,21 +1841,25 @@\n carry = {}\n # Seed carry with the LAST known values BEFORE the grid window starts, so\n # slow pairs (sum renko bricks can be days apart) don't show dashes on\n- # every slot until the next brick prints inside the window. Series come\n- # back DESC from SQL, so the first point with ts < grid[0] is the most\n- # recent one before the window.\n+ # every slot until the next brick prints inside the window. Order-agnostic:\n+ # sort keys, take the last value with ts < window start.\n window_start = grid[0] if grid else None\n def _seed(mp):\n if not window_start:\n return None\n- for ts, v in mp.items(): # DESC order\n- if ts < window_start and v is not None:\n- return v\n- # fall back: first value inside the window\n- for ts in grid:\n- if ts in mp and mp[ts] is not None:\n- return mp[ts]\n- return None\n+ prev_v = None\n+ for ts in sorted(mp.keys()):\n+ if ts < window_start:\n+ if mp[ts] is not None:\n+ prev_v = mp[ts]\n+ else:\n+ break\n+ if prev_v is None:\n+ # nothing known before the window: fall back to first inside\n+ for ts in grid:\n+ if ts in mp and mp[ts] is not None:\n+ return mp[ts]\n+ return prev_v\n for k in (\"ratio\", \"utbot\"):\n mp = {\"ratio\": price_map, \"utbot\": utbot_map}[k]\n v = _seed(mp)\n", "files_modified": ["/tmp/studio_edit.py"], "lint": {"status": "ok", "output": ""}, "resolved_path": "/tmp/studio_edit.py"}
2026-09-07 23:51
ASSISTANT (hermes, glm-5.3-flash)
Now deploy and verify (standard flow: sudo-copy + restart service):
2026-09-07 23:51
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "active", "exit_code": 0, "error": null, "approval": "Command required approval (stop/restart system service) and was approved by the user."}
Dashes are gone — all 200 rows now carry values from the start. Let me also verify the scan endpoint and the cockpit path (scan-all) still work with the correct pair_entry values:
Fixed and verified. One last check — the broker field and armed status so I can report the live state accurately:
2026-09-07 23:52
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "broker: flattrade | armed: True | exec: auto\n{\n \"ts\": \"2026-09-07T23:51:39.453378\",\n \"epoch\": 1788805299.4535253,\n \"market_open\": false,\n \"armed\": [", "exit_code": 0, "error": null, "approval": "Command was flagged (script execution via -e/-c flag) and auto-approved by smart approval."}
2026-09-07 23:52
ASSISTANT (hermes, glm-5.3-flash)
All fixed and verified. Summary:
**Root cause:** the tracking table's carry-forward logic started **empty** at the beginning of its 200-slot window. Your sum pair's renko brick is ₹1000 notional (~0.083%), so INDUSINDBK+TCS sum prints a brick only every few days — the last brick before today was 09-03 09:40, and the next inside the window only landed 09-07 13:40. Result: 175 of 200 rows had no ratio to show (dashes), until carry finally kicked in mid-window.
**Fix:** studio.py `/api/ratiobot/track` now seeds carry with the last known value *before* the window start (fallback to first value inside the window). Deployed, bot-studio restarted, verified:
- 200/200 rows filled, 0 dashes (ratio carries 1220 → 1210 from 09-03 12:05 onward)
- scan endpoint: overall signal = **sell** (15m 3-Candle below UT Bot, state entry — matches your sum-sell config)
- last row 15:40: ratio 1210.0, utbot 1214.4, c15m3 1209.2 — all in the correct thousands display (mult 0.001, kv 5 from the saved pair)
Let me save this pitfall to the skill:
Done. Bot state right now: armed=True, exec=auto, broker=flattrade, signal=sell — market closed so the daemon can't place anything tonight, but since it's armed+auto, tomorrow in the 09:20–15:30 window it will fire on a fresh transition. If you don't want it trading yet, disarm it in the cockpit.
What changed: studio.py track endpoint seeds carry-forward with the last pre-window value (sum bricks print every few days, so the 200-slot window used to start empty → dashes). Skill updated with the pitfall + the pair_entry mult/kv note.
2026-09-07 23:52
USER (hermes, glm-5.3-flash)
why the ratio on charts and on the table is coming differet - check indis-tcs-kotak bot
[Tool: terminal]
{"output": "Error: attempt to write a readonly database\n===\nError: attempt to write a readonly database", "exit_code": 0, "error": null}
The bot's pair_entry says chartMode=renko, brick=0.083 (percent). The stored computed DB uses meta brick_size=10000 (raw ₹10k bricks) — that's likely the divergence. Let me check what the finratio chart actually renders (its JS brick/utbot sources) before concluding:
[Tool: terminal]
{"output": "474:// brick box is a PERCENT of the series price (brick_pct) — a raw-rupee value\n481: if (isPair) return `&brick_pct=${bs}`;\n852: // series price (brick_pct); for plain symbols it's the raw brick_size.\n2:1488: let candles_kv: f64 = params.get(\"keyvalue\").and_then(|s| s.parse().ok()).unwrap_or(10.0);\n6:1894: let kv: f64 = params.get(\"keyvalue\").and_then(|s| s.parse().ok()).unwrap_or(10.0);", "exit_code": 0, "error": null}
2026-09-07 23:58
ASSISTANT (hermes, glm-5.3-flash)
2026-09-07 23:58
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "function getMult() {\n const v = parseFloat(document.getElementById('mult-input').value);\n return (isFinite(v) && v > 0) ? v : 1;\n}\nfunction multParam() { return `&mult=${getMult()}`; }\nfunction multQ() { return `mult=${getMult()}`; }\n// UT Bot Key Value (Pine `a`) — sensitivity of the ATR trailing stop.\nfunction getKV() {\n const v = parseFloat(document.getElementById('kv-input').value);\n return (isFinite(v) && v > 0) ? v : 10;\n}\nfunction kvParam() { return `&keyvalue=${getKV()}`; }\nfunction onKVChange() { isLoading = false; loadAll(); }\n// Brick size param for renko. PAIRS (monetary series, lakhs of rupees): the\n// brick box is a PERCENT of the series price (brick_pct) — a raw-rupee value\n// like 0.5/3 is 0.005/0.03 on a ₹1.35M SUM series → the server OOM guard\n// rejects it → blank chart. Percent is always a sane fraction of the scale.\n// Plain symbols keep the raw brick_size (their series is in single rupees).\nfunction brickParam() {\n const bs = document.getElementById('brick-input').value;\n const isPair = currentSymbol && currentSymbol.includes('-');\n if (isPair) return `&brick_pct=${bs}`;\n return `&brick_size=${bs}`;\n}\n// Update the \"₹1000 ≈ X%\" hint next to the Brick % box. For pairs, the server\n// builds bricks at size = |latestClose| × pct/100, so the pct that gives a\n// ₹1000 brick is 100000/|latestClose|. latestClose is the UNSCALED series\n// close, so we divide the last displayed brick close by the mult.\nfunction updateBrick1000() {\n const el = document.getElementById('brick-1000');\n if (!el) return;\n const isPair = currentSymbol && currentSymbol.includes('-');\n if (!isPair) { el.textContent = '₹1000 ≈ n/a'; return; }\n const bars = chartMode === 'renko' ? (barData && barData.bricks) : (barData && barData.candles);\n if (!bars || bars.length === 0) { el.textContent = '₹1000 ≈ —'; return; }\n const m = getMult();\n731: return `${parts[0]}×${lotOf(parts[0])} ${seriesMode === 'sum' ? '+' : '−'} ${legB}×${lotOf(legB)} ${tag} ×${getMult()}`;\n258:let chartMode = 'renko'; // 'renko' | 'candles'\n275: const days = chartMode === 'candles' ? (document.getElementById('days-input').value || 180) : 365;\n474:// brick box is a PERCENT of the series price (brick_pct) — a raw-rupee value\n481: if (isPair) return `&brick_pct=${bs}`;\n493: const bars = chartMode === 'renko' ? (barData && barData.bricks) : (barData && barData.candles);\n650: chartMode,\n668: setStatus(`Saved \"${name}\" (${getMult()}x, ${document.getElementById('interval-select').value}, ${chartMode})`, 'ok');\n696: const mode = p.chartMode === 'candles' ? 'candles' : 'renko';\n697: chartMode = mode;\n743: chartMode = mode;\n849: if (chartMode === 'renko') {\n852: // series price (brick_pct); for plain symbols it's the raw brick_size.\n879: // Promise order depends on chartMode (see how promises is built):\n891: lastCandleData = chartMode === 'renko' ? results[results.length - 1] :
... [3501 chars total, truncated]
2026-09-07 23:58
ASSISTANT (hermes, glm-5.3-flash)
2026-09-07 23:59
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "fetch(`${API}/snapshots/${currentSymbol}?series=1&limit=300${multParam()}${modeParam()}${kvParam()}`).then(r => { if(!r.ok) throw new Error(`snapshots ${r.status}`); return r.json(); }),\n fetch(`${API}/daily-values/${currentSymbol}?${multQ()}${modeParam()}`).then(r => { if(!r.ok) throw new Error(`daily-values ${r.status}`); return r.json(); }),\n ];\n // Always fetch 15m snapshots for the 15m LIPI/RSI overlay (regardless of chart mode)\n const snap15mPromise = fetch(`${API}/snapshots/${currentSymbol}?series=1&limit=300&interval=15m${multParam()}${modeParam()}${kvParam()}`).then(r => { if(!r.ok) throw new Error(`snapshots 15m ${r.status}`); return r.json(); });\n // 15m candles for the 15m 3-Candle overlay (non-blocking; default days=5 gives ~500 candles = 50 days of 15m window)\n const candles15mPromise = fetch(`${API}/candles/${currentSymbol}?interval=15m&days=30${multParam()}${modeParam()}`).then(r => { if(!r.ok) throw new Error(`candles 15m ${r.status}`); return r.json(); });\n\n let snapIdx = -1;\n if (chartMode === 'renko') {\n const interval = document.getElementById('interval-select').value;\n // Always pass interval. For pairs the brick box is a PERCENT of the\n // series price (brick_pct); for plain symbols it's the raw brick_size.\n // If it matches the server default, Rust reads pre-computed bricks; else\n // it recomputes on the fly for that interval.\n const maxBars0 = parseInt(document.getElementById('bars-input').value) || 300;\n const fetchLimit = Math.max(2000, maxBars0 * 2);\n promises.unshift(fetch(`${API}/bricks/${currentSymbol}?interval=${interval}${brickParam()}&limit=${fetchLimit}${multParam()}${modeParam()}`).then(r => { if(!r.ok) throw new Error(`bricks ${r.status}`); return r.json(); }));\n // Pre-computed snapshots for this interval — capture index (renko array is 5 long)\n snapIdx = promises.push(fetch(`${API}/snapshots/${currentSymbol}?series=1&limit=300&interval=${interval}${multParam()}${modeParam()}${kvParam()}`).then(r => { if(!r.ok) throw new Error(`snapshots ${r.status}`); return r.json(); })) - 1;\n // Raw 5m candle tail — for true last-price legend (renko bricks can legitimately lag)\n promises.push(fetch(`${API}/candles/${currentSymbol}?interval=5m&days=1${multParam()}${modeParam()}`).then(r => { if(!r.ok) throw new Error(`candles ${r.status}`); return r.json(); }));\n } else {\n const interval = document.getElementById('interval-select').value;\n const days = document.getElementById('days-input').value;\n // Candle mode: fetch candles + pre-computed indicators for this interval (two calls)\n promises.unshift(fetch(`${API}/candles/${currentSymbol}?interval=${interval}&days=${days}${multParam()}${modeParam()}`).then(r => { if(!r.ok) throw new Error(`candles ${r.status}`); return r.json(); }));\n // Pre-computed indicators from snapshots table filtered by interval — cap
... [5151 chars total, truncated]
2026-09-07 23:59
ASSISTANT (hermes, glm-5.3-flash)
Now let me check `ensure_fresh_mode` and `pair_brick_size` — I suspect the stored snapshots use a different brick grid than what the chart's brick_pct recomputes:
2026-09-07 23:59
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "", "exit_code": -1, "error": "BLOCKED (hardline): command parser limit or malformed executable payload. This command is on the unconditional blocklist and cannot be executed via the agent — not even with --yolo, /yolo, approvals.mode=off, or cron approve mode. If you genuinely need to run it, run it yourself in a terminal outside the agent. RECOVERY: this block fires on oversized/unparseable inline command payloads (heredocs, giant one-liners), not on the operation itself. Your command was saved to /home/harsheen/.hermes/cache/blocked-scripts/blocked-1788805756-ac5c5cac.sh — review it, then run: terminal(command=\"bash /home/harsheen/.hermes/cache/blocked-scripts/blocked-1788805756-ac5c5cac.sh\"). Do not retry inline.", "status": "blocked"}
[Tool: read_file]
{"content": "240|/// magnitude, so base it on |close|. nice_round() returns 0.01 for any\n241|/// non-positive input, which produced 1-paisa bricks on a ~₹4.5 lakh series\n242|/// and the OOM crash loop of 2026-08-27.\n243|fn pair_brick_size(comp_db: &str, latest_close: f64) -> f64 {\n244| let base = latest_close.abs();\n245| let fallback = nice_round(base * 0.01);\n246| let conn = match Connection::open(comp_db) {\n247| Ok(c) => c,\n248| Err(_) => return fallback,\n249| };\n250| let _ = conn.busy_timeout(Duration::from_secs(15));\n251| let _ = conn.execute_batch(\"CREATE TABLE IF NOT EXISTS meta (key TEXT PRIMARY KEY, value TEXT);\");\n252| let existing: Option<String> = conn\n253| .query_row(\"SELECT value FROM meta WHERE key = 'brick_size'\", [], |r| r.get(0))\n254| .ok();\n255| // Sanity floor: a persisted brick_size is only trustworthy if it is within\n256| // 3 orders of magnitude (≥0.1%) of the series' current scale. A bogus tiny\n257| // value (e.g. 0.01 persisted while the pair series was empty → latest=1.0)\n258| // would rebuild the whole history at 1-paisa bricks = OOM (bug 2026-08-27).\n259| // base is |close| — a NEGATIVE spread must not shrink the floor to 0.01\n260| // (nice_round of a negative returns 0.01), which would re-accept the poison.\n261| let scale_floor = nice_round(base * 0.001);\n262| if let Some(v) = existing {\n263| if let Ok(f) = v.parse::<f64>() {\n264| if f > 0.0 && f >= scale_floor {\n265| return f;\n266| }\n267| }\n268| }\n269| let _ = conn.execute(\n270| \"INSERT OR REPLACE INTO meta (key, value) VALUES ('brick_size', ?)\",\n271| params![fallback.to_string()],\n272| );\n273| fallback\n274|}\n275|\n276|/// Pairs that already have a computed DB in finratio dbs/ → (A, B) uppercase.\n277|fn existing_pairs() -> Vec<(String, String)> {\n278| let mut out: Vec<(String, String)> = Vec::new();\n279| if let Ok(rd) = fs::read_dir(COMPUTED_DB_DIR) {\n280| for e in rd.flatten() {\n281| let name = e.file_name().to_string_lossy().to_string();\n282| let stem = name\n283| .strip_suffix(\"_spread_computed.db\")\n284| .or_else(|| name.strip_suffix(\"_sum_computed.db\"));\n285| if let Some(stem) = stem {\n286| if let Some((a, b)) = stem.split_once('_') {\n287| if !a.is_empty() && !b.is_empty() {\n288| out.push((a.to_uppercase(), b.to_uppercase()));\n289| }\n290| }\n291| }\n292| }\n293| }\n294| out.sort();\n295| out.dedup();\n296| out\n297|}\n298|\n299|// ── Hot/cold watch registry + fill coordination ─────────────────────────────\n300|// HOT_WATCH: symbol -> last heartbeat (frontend POSTs /api/watch every 30s).\n301|// A symbol is HOT while a browser has it open; the watch
... [3901 chars total, truncated]
2026-09-07 23:59
ASSISTANT (hermes, glm-5.3-flash)
2026-09-07 23:59
TOOL (hermes, glm-5.3-flash)
[Tool: read_file]
{"content": "355|}\n356|\n357|/// Reader-endpoint freshness guard: if the computed DB is behind the raw\n358|/// 5-min DB, run an incremental fill synchronously (fast: appends only).\n359|async fn ensure_fresh_mode(sym: &str, mode: PairMode) {\n360| if !computed_stale_mode(sym, mode) {\n361| return;\n362| }\n363| let sym_owned = sym.to_string();\n364| tokio::task::spawn_blocking(move || {\n365| let _g = fill_lock().lock().unwrap();\n366| if !computed_stale_mode(&sym_owned, mode) {\n367| return; // another request just filled it\n368| }\n369| if let Some((a, b)) = parse_pair(&sym_owned) {\n370| let t0 = Instant::now();\n371| match fill_pair_mode(&a, &b, mode) {\n372| Ok((bk, s, d, e)) => println!(\n373| \"[ondemand] {}-{} {} filled: bricks={} snap={} days={} events={} ({:.1}s)\",\n374| a, b, mode.tag(), bk, s, d, e, t0.elapsed().as_secs_f64()\n375| ),\n376| Err(e) => eprintln!(\"[ondemand] {}-{} {} ERROR: {}\", a, b, mode.tag(), e),\n377| }\n378| return;\n379| }\n380| if let Some(cfg) = load_symbols()\n381| .into_iter()\n382| .find(|s| s.name.eq_ignore_ascii_case(&sym_owned))\n383| {\n384| let t0 = Instant::now();\n385| match fill_symbol(&cfg) {\n386| Ok((b, s, d, e)) => println!(\n387| \"[ondemand] {} filled: bricks={} snap={} days={} events={} ({:.1}s)\",\n388| cfg.name, b, s, d, e, t0.elapsed().as_secs_f64()\n389| ),\n390| Err(e) => eprintln!(\"[ondemand] {} ERROR: {}\", cfg.name, e),\n391| }\n392| }\n393| })\n394| .await\n395| .ok();\n396|}\n397|\n398|// ═══════════════════════════════════════════════════════════════════════════\n399|// CANDLE STRUCT\n400|// ═══════════════════════════════════════════════════════════════════════════\n401|\n402|#[derive(Debug, Clone, Serialize, Deserialize)]\n403|pub struct Candle {\n404| pub ts: String,\n405| pub open: f64,\n406| pub high: f64,\n407| pub low: f64,\n408| pub close: f64,\n409| pub volume: f64,\n410|}\n411|\n412|#[derive(Debug, Clone, Serialize)]\n413|pub struct Brick {\n414| pub brick_index: i64,\n415| pub ts: String,\n416| pub open: f64,\n417| pub high: f64,\n418| pub low: f64,\n419| pub close: f64,\n420| pub direction: String,\n421|}\n422|\n423|// ═══════════════════════════════════════════════════════════════════════════\n424|// COMPUTE FUNCTIONS — exact mirrors of app.py math\n425|", "total_lines": 2468, "file_size": 114270, "truncated": true, "hint": "Use offset=425 to continue reading (showing 355-424 of 2468 lines)", "is_binary": false, "is_image": false}
2026-09-07 23:59
ASSISTANT (hermes, glm-5.3-flash)
The chart passes `brick_pct=0.083` (recomputed on the fly) while the stored snapshots sit on `brick_size=10000` (₹10k bricks). Let me confirm how utbot/kv are computed in snapshots vs the fill, since the bot also uses kv=5:
2026-09-07 23:59
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "1488: let candles_kv: f64 = params.get(\"keyvalue\").and_then(|s| s.parse().ok()).unwrap_or(10.0);\n1583: let utbot_series: Vec<Value> = compute_utbot_stop(&utbot_pairs, candles_kv, m).iter()\n1894: let kv: f64 = params.get(\"keyvalue\").and_then(|s| s.parse().ok()).unwrap_or(10.0);\n1973: let utbot_time = compute_utbot_stop(&utbot_pairs, kv, m); // ts -> scaled value", "exit_code": 0, "error": null}
2026-09-07 23:59
ASSISTANT (hermes, glm-5.3-flash)
2026-09-07 23:59
TOOL (hermes, glm-5.3-flash)
[Tool: read_file]
{"content": "1880| scale_fields(val, keys, m);\n1881| }\n1882| }\n1883| }\n1884| Value::Array(arr) => for item in arr.iter_mut() { scale_fields(item, keys, m); },\n1885| _ => {}\n1886| }\n1887|}\n1888|\n1889|async fn api_snapshots(axum::extract::Path(symbol): axum::extract::Path<String>, axum::extract::Query(params): axum::extract::Query<HashMap<String, String>>) -> (StatusCode, Json<Value>) {\n1890| let interval = norm_interval(params.get(\"interval\").map(|s| s.as_str()).unwrap_or(\"5m\"));\n1891| let m = pair_mult(&symbol, ¶ms);\n1892| let mode = PairMode::from_param(params.get(\"mode\"));\n1893| // UT Bot \"Key Value\" multiplier (Pine `a`): default 10. Lower = tighter stop.\n1894| let kv: f64 = params.get(\"keyvalue\").and_then(|s| s.parse().ok()).unwrap_or(10.0);\n1895| ensure_fresh_mode(&symbol, mode).await;\n1896| let conn = match open_computed_mode(&symbol, mode) {\n1897| Some(c) => c,\n1898| None => return (StatusCode::NOT_FOUND, Json(json!({\"status\":\"error\",\"message\":\"computed DB not found\"}))),\n1899| };\n1900| // Latest snapshot\n1901| let latest: Option<Value> = conn.query_row(\n1902| \"SELECT time, ts, price, vidya, sma20, sma50, rsi, atr, macd, macd_signal, macd_hist, stoch_k, stoch_d, computed_at FROM indicator_snapshots WHERE interval = ? ORDER BY time DESC\",\n1903| params![interval], |r| Ok(json!({\n1904| \"time\": r.get::<_, i64>(0)?,\n1905| \"ts\": r.get::<_, String>(1)?,\n1906| \"price\": r.get::<_, Option<f64>>(2)?,\n1907| \"vidya\": r.get::<_, Option<f64>>(3)?,\n1908| \"sma20\": r.get::<_, Option<f64>>(4)?,\n1909| \"sma50\": r.get::<_, Option<f64>>(5)?,\n1910| \"rsi\": r.get::<_, Option<f64>>(6)?,\n1911| \"atr\": r.get::<_, Option<f64>>(7)?,\n1912| \"macd\": r.get::<_, Option<f64>>(8)?,\n1913| \"macd_signal\": r.get::<_, Option<f64>>(9)?,\n1914| \"macd_hist\": r.get::<_, Option<f64>>(10)?,\n1915| \"stoch_k\": r.get::<_, Option<f64>>(11)?,\n1916| \"stoch_d\": r.get::<_, Option<f64>>(12)?,\n1917| \"computed_at\": r.get::<_, String>(13)?,\n1918| }))\n1919| ).ok();\n1920|\n1921| let want_series = params.get(\"series\").map(|s| s == \"1\").unwrap_or(false);\n1922| let mut resp = json!({\n1923| \"status\": \"success\",\n1924| \"symbol\": symbol.to_uppercase(),\n1925| \"interval\": interval,\n1926| \"latest\": latest,\n1927| });\n1928|\n1929| if want_series {\n1930| let limit: i64 = params.get(\"limit\").and_then(|s| s.parse().ok()).unwrap_or(100000);\n1931| let mut stmt = match conn.prepare(\n1932| \"SELECT time, ts, price, vidya, sma20, sma50, rsi, atr, macd, macd_signal, macd_hist, stoch_k, stoch_d FROM indicator_snapshots WHERE interval = ? ORDER
... [9628 chars total, truncated]
2026-09-07 23:59
ASSISTANT (hermes, glm-5.3-flash)
Found the smoking gun: the **stored** computed DB (`indusindbk_tcs_sum_computed.db`) has `meta brick_size = 10000` — snapshots move in ₹10,000-raw steps (1210000 → 1220000 → 1230000). But the **chart** renders bricks with `brick_pct=0.083` (0.083% of ~1.21M ≈ ₹1000 notional) recomputed on the fly. Two different brick grids → different ratio values. Let me verify with the bricks endpoint and check how fill decides to rebuild:
Confirmed the root cause with hard numbers. Chart bricks (0.083% ≈ ₹1000 notional, recomputed per request) vs stored snapshots (meta brick_size=10000 → ₹10k raw bricks = ₹10 displayed). Two different grids. Let me check the scan endpoint's series fetch before proposing the fix:
2026-09-08 00:01
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "", "exit_code": -1, "error": "BLOCKED (hardline): command parser limit or malformed executable payload. This command is on the unconditional blocklist and cannot be executed via the agent — not even with --yolo, /yolo, approvals.mode=off, or cron approve mode. If you genuinely need to run it, run it yourself in a terminal outside the agent. RECOVERY: this block fires on oversized/unparseable inline command payloads (heredocs, giant one-liners), not on the operation itself. Your command was saved to /home/harsheen/.hermes/cache/blocked-scripts/blocked-1788805861-6f7df34d.sh — review it, then run: terminal(command=\"bash /home/harsheen/.hermes/cache/blocked-scripts/blocked-1788805861-6f7df34d.sh\"). Do not retry inline.", "status": "blocked"}
2026-09-08 00:01
ASSISTANT (hermes, glm-5.3-flash)
2026-09-08 00:01
TOOL (hermes, glm-5.3-flash)
[Tool: search_files]
{"total_count": 7, "matches_format": "path-grouped: each file path on its own line, followed by indented '<line>: <content>' rows for matches in that file", "matches_text": "/home/ubuntu/bots/bot-studio/studio.py\n 1474: return False, a, b\n 1475: \n 1476: \n 1477: def _get_series(key, snap, pair, mult, series_mode):\n 1478: \"\"\"Return the full ascending [{ts, value}] series for a trackable.\"\"\"\n 1479: if key == \"price\":\n 1480: return snap.get(\"series\", {}).get(\"price\", [])"}
2026-09-08 00:01
ASSISTANT (hermes, glm-5.3-flash)
2026-09-08 00:01
TOOL (hermes, glm-5.3-flash)
[Tool: read_file]
{"content": "1477|def _get_series(key, snap, pair, mult, series_mode):\n1478| \"\"\"Return the full ascending [{ts, value}] series for a trackable.\"\"\"\n1479| if key == \"price\":\n1480| return snap.get(\"series\", {}).get(\"price\", [])\n1481| elif key == \"3candle\":\n1482| dv = _finratio_get(f\"/api/daily-values/{pair}\", {\"mult\": mult, \"mode\": series_mode})\n1483| rows = dv.get(\"data\", []) if dv.get(\"status\") == \"success\" else []\n1484| return [{\"ts\": r.get(\"date\"), \"value\": r.get(\"three_candle\")}\n1485| for r in rows if r.get(\"three_candle\") is not None]\n1486| elif key == \"15m3candle\":\n1487| cd = _finratio_get(f\"/api/candles/{pair}\",\n1488| {\"interval\": \"15m\", \"days\": 5, \"mult\": mult, \"mode\": series_mode})\n1489| candles = cd.get(\"candles\", []) if cd.get(\"status\") == \"success\" else []\n1490| return _compute_15m3candle(candles)\n1491| else:\n1492| return snap.get(\"series\", {}).get(key, [])\n1493|\n1494|\n1495|def _align_series(series_a, series_b):\n1496| \"\"\"Align two [{ts, value}] series by ts, return list of (a, b) pairs ascending.\"\"\"\n1497| map_b = {p[\"ts\"]: p[\"value\"] for p in series_b}\n1498| pairs = []\n1499| for p in series_a:\n1500| if p[\"ts\"] in map_b and p[\"value\"] is not None and map_b[p[\"ts\"]] is not None:\n1501| pairs.append((p[\"value\"], map_b[p[\"ts\"]]))\n1502| return pairs\n1503|\n1504|\n1505|def _detect_cross(pairs, op, fresh_only=False):\n1506| \"\"\"Scan pairs (ascending) for a sign change.\n1507| cross_above: a went from <= b to > b. cross_below: a went from >= b to < b.\n1508| fresh_only=True: the cross must be on the LATEST bar (i-1 -> i where i is\n1509| the last pair). fresh_only=False: the most recent cross anywhere in the\n1510| window. Returns (bool, cross_index) or (False, None).\"\"\"\n1511| if fresh_only:\n1512| if len(pairs) < 2:\n1513| return False, None\n1514| a_prev, b_prev = pairs[-2]\n1515| a_cur, b_cur = pairs[-1]\n1516| if op == \"cross_above\" and a_prev <= b_prev and a_cur > b_cur:\n1517| return True, len(pairs) - 1\n1518| if op == \"cross_below\" and a_prev >= b_prev and a_cur < b_cur:\n1519| return True, len(pairs) - 1\n1520| return False, None\n1521| for i in range(len(pairs) - 1, 0, -1):\n1522| a_prev, b_prev = pairs[i - 1]\n1523| a_cur, b_cur = pairs[i]\n1524| if op == \"cross_above\" and a_prev <= b_prev and a_cur > b_cur:\n1525| return True, i\n1526| if op == \"cross_below\" and a_prev >= b_prev and a_cur < b_cur:\n1527| return True, i\n1528| return False, None\n1529|\n1530|\n1531|def _build_legs(cfg, signal):\n1532|", "total_lines": 2242, "file_size": 95719, "truncated": true, "hint": "Use offset=1532 to continue reading (showi
... [3068 chars total, truncated]
2026-09-08 00:01
ASSISTANT (hermes, glm-5.3-flash)
2026-09-08 00:01
TOOL (hermes, glm-5.3-flash)
[Tool: search_files]
{"total_count": 9, "matches_format": "path-grouped: each file path on its own line, followed by indented '<line>: <content>' rows for matches in that file", "matches_text": "/home/ubuntu/bots/bot-studio/studio.py\n 1598: return jsonify({\"status\": \"success\", \"pair\": pair})\n 1599: \n 1600: \n 1601: @app.route(\"/api/ratiobot/scan\", methods=[\"POST\"])\n 1602: def api_ratiobot_scan():\n 1603: \"\"\"Evaluate the pair's conditions against current finratio values.\"\"\"\n 1604: data = request.get_json(force=True) or {}\n 1605: a = (data.get(\"a\") or \"\").strip().upper()\n 1606: b = (data.get(\"b\") or \"\").strip().upper()"}
2026-09-08 00:01
ASSISTANT (hermes, glm-5.3-flash)
2026-09-08 00:01
TOOL (hermes, glm-5.3-flash)
[Tool: read_file]
{"content": "1601|@app.route(\"/api/ratiobot/scan\", methods=[\"POST\"])\n1602|def api_ratiobot_scan():\n1603| \"\"\"Evaluate the pair's conditions against current finratio values.\"\"\"\n1604| data = request.get_json(force=True) or {}\n1605| a = (data.get(\"a\") or \"\").strip().upper()\n1606| b = (data.get(\"b\") or \"\").strip().upper()\n1607| if not a or not b:\n1608| return jsonify({\"status\": \"error\", \"message\": \"a and b required\"}), 400\n1609| pair = f\"{a}-{b}\"\n1610| mode = data.get(\"mode\", \"spread\")\n1611| series_mode = \"sum\" if mode == \"sum\" else \"spread\"\n1612| mult = float(data.get(\"mult\", 100))\n1613| interval = data.get(\"interval\", \"5m\")\n1614| kv = float(data.get(\"kv\", 10))\n1615| conditions = data.get(\"conditions\", [])\n1616|\n1617| snap = _finratio_get(f\"/api/snapshots/{pair}\",\n1618| {\"series\": 1, \"limit\": 300, \"mult\": mult,\n1619| \"mode\": series_mode, \"keyvalue\": kv})\n1620| if snap.get(\"status\") != \"success\":\n1621| return jsonify({\"status\": \"error\", \"message\": snap.get(\"message\", \"snapshots failed\")}), 502\n1622| latest = snap.get(\"latest\") or {}\n1623| series = snap.get(\"series\") or {}\n1624|\n1625| values = {}\n1626| for key, meta in TRACKABLES.items():\n1627| if key == \"price\":\n1628| values[\"price\"] = latest.get(\"price\")\n1629| elif key == \"3candle\":\n1630| dv = _finratio_get(f\"/api/daily-values/{pair}\", {\"mult\": mult, \"mode\": series_mode})\n1631| rows = dv.get(\"data\", []) if dv.get(\"status\") == \"success\" else []\n1632| last = rows[-1] if rows else {}\n1633| values[\"3candle\"] = last.get(\"three_candle\")\n1634| elif key == \"15m3candle\":\n1635| cd = _finratio_get(f\"/api/candles/{pair}\",\n1636| {\"interval\": \"15m\", \"days\": 5, \"mult\": mult, \"mode\": series_mode})\n1637| candles = cd.get(\"candles\", []) if cd.get(\"status\") == \"success\" else []\n1638| line = _compute_15m3candle(candles)\n1639| values[\"15m3candle\"] = line[-1][\"value\"] if line else None\n1640| else:\n1641| s = series.get(key) or []\n1642| values[key] = s[-1][\"value\"] if s else None\n1643|\n1644| cond_results = []\n1645| for c in conditions:\n1646| op = c.get(\"op\")\n1647| track = c.get(\"trackable\")\n1648| target = c.get(\"target\")\n1649| sig = c.get(\"signal\", \"buy\") # \"buy\" | \"sell\"\n1650| # Target may be a number OR another trackable name (e.g. \"utbot\")\n1651| target_is_trackable = isinstance(target, str) and target in TRACKABLES\n1652| if op in (\"cross_above\", \"cross_below\"):\n1653| # Build the two series and detect the sign change\n1654| sa = _get_series(
... [5106 chars total, truncated]
2026-09-08 00:01
ASSISTANT (hermes, glm-5.3-flash)
The scan card's "price" value also comes from the same stored snapshots — so both the signal card and tracking table show the stored ₹10k-grid ratio, while the chart recomputes 0.083% bricks. Before fixing, let me check what the daemon and the builder page send:
2026-09-08 00:03
TOOL (hermes, glm-5.3-flash)
[Tool: search_files]
{"total_count": 41, "matches_format": "path-grouped: each file path on its own line, followed by indented '<line>: <content>' rows for matches in that file", "matches_text": "/home/ubuntu/bots/bot-studio/ratiobot_daemon.py\n 3: \n 4: Runs whether or not any browser page is open. Every 2.5 min it:\n 5: - scans each ARMED bot (bot-studio /api/ratiobot/scan)\n 6: - records signal transitions in ratiobot_signals.jsonl\n 7: - if the bot's exec mode is AUTO and a fresh transition printed:\n 16: \n 17: Test flags: --once (single cycle), --force (bypass market-hours gate for\n 18: scanning; orders remain gated by rails 2 and 4, so --force is order-safe).\n 19: \"\"\"\n 20: import json\n 67: \n 68: \n 69: def scan_body(cfg):\n 70: pe = cfg.get(\"pair_entry\", {})\n 71: \n 88: \n 89: def place_orders(cfg, signal):\n 90: body = {\n 91: \"a\": cfg.get(\"a\"), \"b\": cfg.get(\"b\"),\n 92: \"mode\": cfg.get(\"mode\", \"spread\"),\n 95: \"signal\": signal,\n 96: }\n 97: r = requests.post(f\"{BASE}/api/ratiobot/place\", json=body, timeout=20)\n 98: return r.json()\n 99: \n 154: continue\n 155: try:\n 156: r = requests.post(f\"{BASE}/api/ratiobot/scan\",\n 157: json=scan_body(cfg), timeout=30)\n 158: scan = r.json()\n 159: if scan.get(\"status\") != \"success\":\n 160: log(f\"{name}: scan error: {scan.get('message')}\")\n 161: continue\n 162: signal = scan.get(\"signal\") # 'buy' | 'sell' | None\n 163: rec = dstate.get(name, {})\n 164: first_seen = \"last_signal\" not in rec\n 165: last = rec.get(\"last_signal\")\n 166: rec[\"last_signal\"] = signal\n 167: rec[\"last_scan\"] = dt.isoformat()\n 168: dstate[name] = rec\n 169: "}
Full picture confirmed. Now I understand exactly why the chart and table disagree:
**Root cause — two different brick grids:**
- The **chart** always sends `brick_pct=0.083` → finratio recomputes renko bricks on the fly at 0.083% of latest sum (≈ ₹1000 raw ≈ ₹1.00 displayed) — dense grid: 1206.52, 1207.52, 1208.53, 1209.53…
- The **bot's scan/track table** reads the **stored** `indicator_snapshots` in `indusindbk_tcs_sum_computed.db`, which sits on `meta brick_size=10000` (₹10k raw = ₹10 displayed) — coarse grid: 1210, 1220, 1230, only printing every few days.
So the table's Ratio comes from a ₹10k-brick grid while the chart draws a ₹1000-brick grid. UT Bot and 15m 3-Candle already agree (both computed from time candles, not the brick grid) — only the ratio diverges.
Fix: when a bot is renko with a brick %, source the ratio series from the same `/api/bricks?brick_pct=` endpoint the chart uses. Patching:
[Tool: search_files]
{"total_count": 34, "matches_format": "path-grouped: each file path on its own line, followed by indented '<line>: <content>' rows for matches in that file", "matches_text": "/tmp/studio_edit2.py\n 1609: pair = f\"{a}-{b}\"\n 1610: mode = data.get(\"mode\", \"spread\")\n 1611: series_mode = \"sum\" if mode == \"sum\" else \"spread\"\n 1612: mult = float(data.get(\"mult\", 100))\n 1613: interval = data.get(\"interval\", \"5m\")\n 1614: kv = float(data.get(\"kv\", 10))\n 1615: conditions = data.get(\"conditions\", [])\n 1616: \n 1617: snap = _finratio_get(f\"/api/snapshots/{pair}\",\n 1618: {\"series\": 1, \"limit\": 300, \"mult\": mult,\n 1619: \"mode\": series_mode, \"keyvalue\": kv})\n 1620: if snap.get(\"status\") != \"success\":\n 1621: return jsonify({\"status\": \"error\", \"message\": snap.get(\"message\", \"snapshots failed\")}), 502\n 1622: latest = snap.get(\"latest\") or {}\n 1623: series = snap.get(\"series\") or {}\n 1624: \n 1625: values = {}\n 1729: series_mode = \"sum\" if mode == \"sum\" else \"spread\"\n 1730: mult = float(data.get(\"mult\", 100))\n 1731: interval = data.get(\"interval\", \"5m\")\n 1732: kv = float(data.get(\"kv\", 10))\n 1733: broker = data.get(\"broker\", \"kotak\")\n 1734: conditions = data.get(\"conditions\", [])\n 1735: \n 1736: # Per-candle series from finratio snapshots (5m base)\n 1737: snap = _finratio_get(f\"/api/snapshots/{pair}\",\n 1738: {\"series\": 1, \"limit\": 300, \"mult\": mult,\n 1739: \"mode\": series_mode, \"keyvalue\": kv, \"interval\": \"5m\"})\n 1740: if snap.get(\"status\") != \"success\":\n 1741: return jsonify({\"status\": \"error\", \"message\": snap.get(\"message\", \"snapshots failed\")}), 502\n 1742: series = snap.get(\"series\") or {}\n 1743: price_s = series.get(\"price\", [])\n 1744: utbot_s = series.get(\"utbot\", [])\n 1745: "}
2026-09-08 00:05
ASSISTANT (hermes, glm-5.3-flash)
Now let me check `_finratio_get` and then write the patch:
2026-09-08 00:06
TOOL (hermes, glm-5.3-flash)
[Tool: search_files]
{"total_count": 21, "matches_format": "path-grouped: each file path on its own line, followed by indented '<line>: <content>' rows for matches in that file", "matches_text": "/tmp/studio_edit2.py\n 1367: except Exception:\n 1368: return {}\n 1369: return {}\n 1370: \n 1371: \n 1372: def _save_ratiobot_state(state):\n 1373: with open(RATIOBOT_STATE, \"w\") as f:\n 1374: json.dump(state, f, indent=2)\n 1375: \n 1376: \n 1377: def _finratio_get(path, params=None):\n 1378: try:\n 1379: r = _requests.get(f\"{FINRATIO}{path}\", params=params, timeout=10)\n 1380: return r.json()\n 1381: except Exception as e:\n 1382: return {\"status\": \"error\", \"message\": str(e)}\n 1383: \n 1384: \n 1385: def _finratio_post(path, body):\n 1386: try:\n 1387: r = _requests.post(f\"{FINRATIO}{path}\", json=body, timeout=10)"}
2026-09-08 00:06
ASSISTANT (hermes, glm-5.3-flash)
2026-09-08 00:06
TOOL (hermes, glm-5.3-flash)
[Tool: patch]
{"success": true, "diff": "--- a//tmp/studio_edit2.py\n+++ b//tmp/studio_edit2.py\n@@ -1380,6 +1380,42 @@\n return r.json()\n except Exception as e:\n return {\"status\": \"error\", \"message\": str(e)}\n+\n+\n+def _override_price_with_bricks(snap, pair, series_mode, mult, interval,\n+ chart_mode, brick, bars):\n+ \"\"\"Renko pair bots: source the ratio (price) series from /api/bricks with\n+ brick_pct — the SAME on-the-fly grid the chart renders — instead of the\n+ stored indicator_snapshots (whose meta brick_size can be a totally\n+ different grid, e.g. ₹10k stored vs 0.083% ≈ ₹1k displayed → chart and\n+ table disagree). Only for renko bots with a positive brick %. No-op on\n+ failure (falls back to snapshots).\"\"\"\n+ if chart_mode and chart_mode != \"renko\":\n+ return\n+ try:\n+ bp = float(brick)\n+ except (TypeError, ValueError):\n+ return\n+ if not bp or bp <= 0:\n+ return\n+ try:\n+ lim = max(2000, int(float(bars or 300)) * 2)\n+ except (TypeError, ValueError):\n+ lim = 4000\n+ br = _finratio_get(f\"/api/bricks/{pair}\",\n+ {\"interval\": interval or \"5m\", \"brick_pct\": bp,\n+ \"limit\": lim, \"mult\": mult, \"mode\": series_mode})\n+ if br.get(\"status\") != \"success\":\n+ return\n+ pts = []\n+ for b in (br.get(\"bricks\") or []):\n+ ts, v = b.get(\"ts\"), b.get(\"close\")\n+ if ts and v is not None:\n+ pts.append({\"ts\": ts, \"value\": v})\n+ if not pts:\n+ return\n+ snap.setdefault(\"series\", {})[\"price\"] = pts\n+ snap[\"price_source\"] = \"bricks_brick_pct\"\n \n \n def _finratio_post(path, body):\n", "files_modified": ["/tmp/studio_edit2.py"], "lint": {"status": "ok", "output": ""}, "resolved_path": "/tmp/studio_edit2.py"}
[Tool: terminal]
{"output": "compile-ok\nactive\nactive", "exit_code": 0, "error": null, "approval": "Command was flagged (stop/restart system service) and auto-approved by smart approval."}
2026-09-08 00:07
ASSISTANT (hermes, glm-5.3-flash)
Now verify the kotak sum-sell bot's track table matches the chart grid:
Table now shows exactly the chart's brick closes (1206.520…, 1208.527…, 1209.531… — identical to the `/api/bricks?brick_pct=0.083` output). Final verification — scan card + cockpit scan-all + daemon:
2026-09-08 00:07
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "scan status: success | overall: sell\n cond: 15m 3-Candle crosses below UT Bot | a_val: 1209.1661250000002 | b_val: 1214.367 | true: True\nINDUSINDBK-TCS: track rows 200, ratio None 0, last ratio 187.54944000000123, sig neutral\nINDUSINDBK-TCS-sum sell kotak: track rows 200, ratio None 0, last ratio 1209.5314024999889, sig sell\n{\n \"ts\": \"2026-09-08T00:07:35.139875\",\n \"epoch\": 1788806255.139994,\n \"market_open\": false,\n \"armed\": [\n \"INDUSINDBK-TCS\"\n ]\n}", "exit_code": 0, "error": null, "approval": "Command was flagged (script execution via heredoc) and auto-approved by smart approval."}
2026-09-08 00:08
ASSISTANT (hermes, glm-5.3-flash)
All verified. Summary:
**Why the chart and table disagreed:** two different renko brick grids.
- The **chart** always recomputes bricks on the fly with `brick_pct=0.083` (≈₹1000 notional → ₹1.00 displayed steps: 1206.52, 1207.52, 1208.53…)
- The **bot's scan/track table** read the stored `indicator_snapshots`, which sit on `meta brick_size=10000` (₹10k raw → ₹10 displayed steps: 1210, 1220, 1230, printing only every few days)
Same pair, different grids → different ratio values. UT Bot and 15m 3-Candle were never affected (both are computed from time candles, not the brick grid).
**Fix (deployed + verified):**
- studio.py: new `_override_price_with_bricks()` — for renko bots with a brick %, scan and track now source the ratio series from `/api/bricks?brick_pct=` — the exact same grid the chart renders. Falls back to snapshots on any failure.
- Cockpit scan-all + daemon `scan_body` now pass chartMode/brick/bars from pair_entry, so all three callers (browser builder, cockpit, daemon) see the chart's grid.
- Verified: table rows now show the chart's brick closes exactly (1209.53 at 15:40 vs chart's last brick 1209.5314); scan card a_val = same value; both bots 200/200 rows, 0 dashes; daemon heartbeat fresh and picking up both armed bots.
Also worth knowing: the stored `indusindbk_tcs_sum_computed.db` snapshots (and its meta brick_size=10000) don't match the chart's 0.083% — that's a finratio-side quirk, harmless now that bots bypass it for renko bots. Let me update the skill:
Fixed. The ratio mismatch was two different renko brick grids — chart used brick_pct=0.083 (₹1 displayed steps) while the bot table read stored snapshots on a ₹10k raw brick (₹10 displayed steps). Now scan, track, cockpit, and the daemon all read the same /api/bricks?brick_pct= grid the chart draws, verified row-for-row (15:40 row = 1209.5314 = chart's last brick).
2026-09-08 00:08
USER (hermes, glm-5.3-flash)
so now going forward in any chart and the tabke will match ??
2026-09-08 00:14
ASSISTANT (hermes, glm-5.3-flash)
Yes — with clear boundaries:
**What's guaranteed now:** scan card, tracking table, cockpit, and the daemon all read the ratio from the same `/api/bricks?brick_pct=` series the chart draws, using each bot's own saved interval/brick. This covers all 3 current bots and any new bot you save (the save button already stores chartMode/brick/bars in pair_entry). Verified row-for-row on the kotak sum bot: table 15:40 row = 1209.5314 = chart's last brick.
**The match holds when the chart is viewed at the bot's saved settings** — renko, interval 5m, brick 0.083 (sum bot) / 0.52 (spread bot), mult 0.001, kv 5. Those are exactly what auto-fill when you load the saved pair. If you manually fiddle interval/brick/kv on the chart, they'll legitimately differ — the table always reflects the bot's config, not whatever the chart happens to show.
**Two small caveats:**
- UT Bot line on the chart follows the kv box in the browser; the table uses the bot's kv (5). Keep the chart kv at 5 and the lines match.
- Candle-chart bots: none exist right now. If you ever save one, its ratio column would still come from the stored snapshots (old behavior). Say the word and I'll extend the same parity to candle mode (source the time candles instead) — it's a small patch.
2026-09-08 00:14
USER (hermes, glm-5.3-flash)
but the candles only have mult factor
2026-09-08 00:16
ASSISTANT (hermes, glm-5.3-flash)
Right — candle charts have no brick grid at all, just the time candles × mult. So for candle-mode bots the table should source the ratio from `/api/candles` closes — trivial exact parity. Patching that in now:
[Tool: patch]
{"success": true, "diff": "--- a//tmp/studio_edit3.py\n+++ b//tmp/studio_edit3.py\n@@ -1388,15 +1388,30 @@\n brick_pct — the SAME on-the-fly grid the chart renders — instead of the\n stored indicator_snapshots (whose meta brick_size can be a totally\n different grid, e.g. ₹10k stored vs 0.083% ≈ ₹1k displayed → chart and\n- table disagree). Only for renko bots with a positive brick %. No-op on\n- failure (falls back to snapshots).\"\"\"\n- if chart_mode and chart_mode != \"renko\":\n+ table disagree). Candle pair bots: source it from /api/candles closes —\n+ candles carry only the mult factor, so parity is exact by construction.\n+ No-op on failure (falls back to snapshots).\"\"\"\n+ if not chart_mode:\n+ return # renko is the default; an absent chartMode keeps old behavior\n+ try:\n+ bp = float(brick) if brick not in (None, \"\") else None\n+ except (TypeError, ValueError):\n+ bp = None\n+ if chart_mode == \"candles\":\n+ cd = _finratio_get(f\"/api/candles/{pair}\",\n+ {\"interval\": interval or \"5m\", \"days\": 10,\n+ \"mult\": mult, \"mode\": series_mode})\n+ if cd.get(\"status\") != \"success\":\n+ return\n+ pts = [{\"ts\": c[\"ts\"], \"value\": c[\"close\"]}\n+ for c in (cd.get(\"candles\") or [])\n+ if c.get(\"ts\") and c.get(\"close\") is not None]\n+ if not pts:\n+ return\n+ snap.setdefault(\"series\", {})[\"price\"] = pts\n+ snap[\"price_source\"] = \"candles\"\n return\n- try:\n- bp = float(brick)\n- except (TypeError, ValueError):\n- return\n- if not bp or bp <= 0:\n+ if chart_mode != \"renko\" or not bp or bp <= 0:\n return\n try:\n lim = max(2000, int(float(bars or 300)) * 2)\n", "files_modified": ["/tmp/studio_edit3.py"], "lint": {"status": "ok", "output": ""}, "resolved_path": "/tmp/studio_edit3.py"}
2026-09-08 00:17
ASSISTANT (hermes, glm-5.3-flash)
2026-09-08 00:17
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "active", "exit_code": 0, "error": null, "approval": "Command required approval (stop/restart system service) and was approved by the user."}
2026-09-08 00:20
ASSISTANT (hermes, glm-5.3-flash)
2026-09-08 00:20
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "RENGO bot: rows 200 | ratio None: 0 | last ratio: 1209.5314024999889\nCANDLE bot: rows 200 | ratio None: 0 | last 3:\n 2026-09-07 15:30:00 | ratio: 1209.3500000000001\n 2026-09-07 15:35:00 | ratio: 1209.3500000000001\n 2026-09-07 15:40:00 | ratio: 1209.3500000000001\nchart last candle close: 1209.3500000000001 | table last ratio: 1209.3500000000001 | match: True", "exit_code": 0, "error": null, "approval": "Command was flagged (script execution via heredoc) and auto-approved by smart approval."}
Done. Yes — now both modes match, going forward:
- **Renko bots** (like your two INDUSINDBK-TCS bots): table ratio = chart's brick_pct grid. Regression-tested after this change — kotak sum bot still shows 1209.5314, identical to the chart's last brick.
- **Candle bots**: candles only carry the mult factor, so the table now reads the ratio straight from `/api/candles` closes — exact match by construction. Tested with a simulated candle-mode bot on the same pair: table last ratio 1209.35 = chart's last candle close 1209.35, byte-for-byte.
The match holds as long as the chart is viewed at the bot's saved settings (which auto-fill when you load the saved pair). Any new bot you save — renko or candles — gets parity automatically since save stores chartMode/brick/bars and scan/track/cockpit/daemon all pass them through.
2026-09-08 00:20
USER (hermes, glm-5.3-flash)
can you check how many bots are runnng at backend ?
2026-09-08 00:22
ASSISTANT (hermes, glm-5.3-flash)
2026-09-08 00:23
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "INDUSINDBK-TCS | armed: True | exec: auto | broker: flattrade\nINDUSINDBK-TCS-sum sell kotak | armed: False | exec: auto | broker: kotak\n---\n{\n \"ts\": \"2026-09-08T00:22:35.146492\",\n \"epoch\": 1788807155.1468823,\n \"market_open\": false,\n \"armed\": [\n \"INDUSINDBK-TCS\"\n ]\n}---\nactive\nactive\n---\nubuntu 2117765 0.0 0.0 39840 27792 ? Ss 00:07 0:00 /usr/bin/python3 /home/ubuntu/bots/bot-studio/ratiobot_daemon.py\nubuntu 2136047 0.7 0.1 136252 58332 ? Ss 00:20 0:01 /usr/bin/python3 /home/ubuntu/bots/bot-studio/studio.py", "exit_code": 0, "error": null, "approval": "Command was flagged (script execution via heredoc) and auto-approved by smart approval."}
2026-09-08 00:23
ASSISTANT (hermes, glm-5.3-flash)
2 bots saved, **1 actively running (armed)**:
| Bot | Broker | Mode | Armed | Exec |
|---|---|---|---|---|
| INDUSINDBK-TCS | flattrade | spread, buy-only | **YES — running** | auto |
| INDUSINDBK-TCS-sum sell kotak | kotak | sum, sell-only | no — disarmed | auto |
Backend processes (both healthy):
- **ratiobot-daemon** — active, last heartbeat 00:22 (scans every 2.5 min; currently sees only INDUSINDBK-TCS as armed)
- **bot-studio** (Flask on 5302) — active
So only INDUSINDBK-TCS will fire orders tomorrow in the 09:20–15:30 window (it's armed + auto). The sum-sell kotak bot is disarmed — it only scans, places nothing. Market is closed right now, so nothing can trigger until 09:20 tomorrow.
2026-09-08 00:23
USER (hermes, glm-5.3-flash)
and now
2026-09-08 00:24
ASSISTANT (hermes, glm-5.3-flash)
2026-09-08 00:24
TOOL (hermes, glm-5.3-flash)
[Tool: terminal]
{"output": "INDUSINDBK-TCS | armed: True | exec: auto | broker: flattrade\nINDUSINDBK-TCS-sum sell kotak | armed: True | exec: auto | broker: kotak\n---\n{\n \"ts\": \"2026-09-08T00:22:35.146492\",\n \"epoch\": 1788807155.1468823,\n \"market_open\": false,\n \"armed\": [\n \"INDUSINDBK-TCS\"\n ]\n}---\nactive\nactive", "exit_code": 0, "error": null, "approval": "Command was flagged (script execution via heredoc) and auto-approved by smart approval."}
2026-09-08 00:24
ASSISTANT (hermes, glm-5.3-flash)
Both bots are now armed:
| Bot | Broker | Mode | Armed | Exec |
|---|---|---|---|---|
| INDUSINDBK-TCS | flattrade | spread, buy-only | **YES** | auto |
| INDUSINDBK-TCS-sum sell kotak | kotak | sum, sell-only | **YES** (just armed) | auto |
The daemon heartbeat (00:22) still lists only the first bot — it re-reads state each cycle, so by ~00:25 it'll pick up the kotak bot too. From tomorrow 09:20, both are live: flattrade bot can fire BUY legs, kotak bot can fire SELL legs on their respective signals.
2026-09-08 00:24
USER (hermes, glm-5.3-flash)
one LAST THING - my harsheen linux is running 11.2 g memory - i wonder why
Your memory is fine — the monitor's "11.2 GB used" is only about a third of the story. Real picture: **31 GB total, ~10-11 GB actually used by processes, 20 GB is buff/cache** (Linux keeps free RAM as disk cache; it instantly frees when anything needs it — "available" is 20 GB).
What's actually eating it (top offenders):
| Process | RAM | What |
|---|---|---|
| chart-data-api gunicorn (2 workers) | ~3.4 GB | port 5050 values-DB reader — biggest single item |
| 3 OpenAlgo brokers (flattrade/shoonya/kotak) | ~1.6 GB | your live broker instances, needed |
| 3 Hermes agent sessions | ~1.2 GB | pts/0 + pts/1 + pts/2 — you have three running |
| finratio (Rust) | ~460 MB | chart server 5202 |
| gnome-system-monitor | ~445 MB | ironically the monitor itself, 6.6% CPU |
| gnome-shell + rustdesk + dsh web | ~860 MB | desktop + remote access |
So: ~3.4 GB is the chart API, and the rest is your full trading stack — nothing is leaking or runaway. If you ever want to trim: closing idle Hermes terminal sessions (~800 MB) and the gnome-system-monitor (445 MB) are the easy wins; the chart API's 2 gunicorn workers could go to 1 if you want (halves its 3.4 GB, slightly slower chart loads). Want me to do any of that?
2026-09-08 00:26
USER (hermes, glm-5.3-flash)
no its fine
2026-09-08 00:27
ASSISTANT (hermes, glm-5.3-flash)
👍 All good — nothing to change. The 11.2 GB reading is normal (10 GB processes + the rest is reclaimable cache); with 20 GB still available, the laptop has plenty of headroom for the trading stack and tomorrow's live bots.