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range: string } {\n const map: Record = {\n \"1m\": { interval: \"1m\", range: \"1d\" },\n \"5m\": { interval: \"5m\", range: \"5d\" },\n \"15m\": { interval: \"15m\", range: \"1mo\" },\n \"1H\": { interval: \"60m\", range: \"3mo\" },\n \"4H\": { interval: \"1h\", range: \"6mo\" },\n \"1D\": { interval: \"1d\", range: \"1y\" },\n \"1W\": { interval: \"1wk\", range: \"2y\" },\n \"1M\": { interval: \"1mo\", range: \"5y\" },\n };\n return map[tf] ?? { interval: \"1d\", range: \"6mo\" };\n}\n\n// ─── Tool: search_symbols ────────────────────────────────────────────\nexport async function searchSymbols(query: string): Promise {\n try {\n const res = await fetch(\n `${YF_BASE}/search?q=${encodeURIComponent(query)}"esCount=10&newsCount=0`,\n { headers: { \"User-Agent\": \"Mozilla/5.0\" } },\n );\n const data = await res.json();\n return (data.quotes || []).map((q: any) => ({\n symbol: q.symbol,\n name: q.shortname || q.longname || q.symbol,\n exchange: q.exchange,\n type: q.quoteType,\n region: q.region ?? \"US\",\n }));\n } catch (e) {\n return [{ error: `Search failed: ${e.message}` }];\n }\n}\n\n// ─── Tool: get_quote ─────────────────────────────────────────────────\nexport async function getQuote(symbol: string): Promise {\n try {\n const sym = normalizeSymbol(symbol);\n const res = await fetch(\n `https://query1.finance.yahoo.com/v7/finance/quote?symbols=${encodeURIComponent(sym)}`,\n { headers: { \"User-Agent\": \"Mozilla/5.0\" } },\n );\n const data = await res.json();\n const q = data.quoteResponse?.result?.[0];\n if (!q) return { error: `No quote found for ${symbol}` };\n return {\n symbol: q.symbol,\n name: q.shortName ?? q.longName ?? q.symbol,\n price: q.regularMarketPrice,\n change: q.regularMarketChange,\n changePercent: q.regularMarketChangePercent,\n previousClose: q.regularMarketPreviousClose,\n open: q.regularMarketOpen,\n high: q.regularMarketDayHigh,\n low: q.regularMarketDayLow,\n volume: q.regularMarketVolume,\n marketCap: q.marketCap,\n currency: q.currency,\n };\n } catch (e) {\n return { error: `Quote failed: ${e.message}` };\n }\n}\n\n// ─── Tool: get_quotes_batch ──────────────────────────────────────────\nexport async function getQuotesBatch(symbols: string[]): Promise {\n const results = await Promise.all(symbols.map((s) => getQuote(s)));\n return results;\n}\n\n// ─── Tool: get_ohlcv ─────────────────────────────────────────────────\nexport async function getOHLCV(\n symbol: string,\n timeframe: string = \"1D\",\n limit: number = 100,\n): Promise {\n try {\n const sym = normalizeSymbol(symbol);\n const { interval, range } = timeframeToInterval(timeframe);\n const url = `${YF_CHART}/${encodeURIComponent(sym)}?interval=${interval}&range=${range}&includePrePost=false`;\n const res = await fetch(url, { headers: { \"User-Agent\": \"Mozilla/5.0\" } });\n const data = await res.json();\n const result = data.chart?.result?.[0];\n if (!result) return { error: `No OHLCV data for ${symbol}` };\n\n const timestamps = result.timestamp || [];\n const quotes = result.indicators?.quote?.[0] || {};\n const bars = [];\n const startIdx = Math.max(0, timestamps.length - limit);\n for (let i = startIdx; i < timestamps.length; i++) {\n if (quotes.open?.[i] != null) {\n bars.push({\n timestamp: new Date(timestamps[i] * 1000).toISOString(),\n open: quotes.open[i],\n high: quotes.high[i],\n low: quotes.low[i],\n close: quotes.close[i],\n volume: quotes.volume?.[i] ?? 0,\n });\n }\n }\n return { symbol: sym, timeframe, bars, count: bars.length };\n } catch (e) {\n return { error: `OHLCV failed: ${e.message}` };\n }\n}\n\n// ─── Tool: get_technicals ────────────────────────────────────────────\nexport async function getTechnicals(symbol: string, timeframe: string = \"1D\"): Promise {\n try {\n const ohlcv = await getOHLCV(symbol, timeframe, 200);\n if (ohlcv.error) return ohlcv;\n const bars = ohlcv.bars;\n const closes = bars.map((b: any) => b.close);\n const highs = bars.map((b: any) => b.high);\n const lows = bars.map((b: any) => b.low);\n const volumes = bars.map((b: any) => b.volume);\n\n const last = closes[closes.length - 1];\n\n // Simple Moving Averages\n const sma = (period: number) => {\n if (closes.length < period) return null;\n const slice = closes.slice(-period);\n return slice.reduce((a: number, b: number) => a + b, 0) / period;\n };\n // Exponential Moving Averages\n const ema = (period: number) => {\n if (closes.length < period) return null;\n const k = 2 / (period + 1);\n let emaVal = closes.slice(0, period).reduce((a: number, b: number) => a + b, 0) / period;\n for (let i = period; i < closes.length; i++) {\n emaVal = closes[i] * k + emaVal * (1 - k);\n }\n return emaVal;\n };\n // RSI\n const rsi = (period: number = 14) => {\n if (closes.length < period + 1) return null;\n let gains = 0, losses = 0;\n for (let i = closes.length - period; i < closes.length; i++) {\n const diff = closes[i] - closes[i - 1];\n if (diff > 0) gains += diff; else losses -= diff;\n }\n const avgGain = gains / period;\n const avgLoss = losses / period;\n if (avgLoss === 0) return 100;\n const rs = avgGain / avgLoss;\n return 100 - (100 / (1 + rs));\n };\n // MACD\n const macd = () => {\n const ema12 = ema(12);\n const ema26 = ema(26);\n if (!ema12 || !ema26) return null;\n const macdLine = ema12 - ema26;\n const signalLine = macdLine * 0.9; // simplified\n return { macd: macdLine, signal: signalLine, histogram: macdLine - signalLine };\n };\n // Bollinger Bands\n const bollinger = (period: number = 20) => {\n if (closes.length < period) return null;\n const slice = closes.slice(-period);\n const smaVal = slice.reduce((a: number, b: number) => a + b, 0) / period;\n const variance = slice.reduce((a: number, b: number) => a + (b - smaVal) ** 2, 0) / period;\n const std = Math.sqrt(variance);\n return {\n middle: smaVal,\n upper: smaVal + 2 * std,\n lower: smaVal - 2 * std,\n };\n };\n // ATR\n const atr = (period: number = 14) => {\n if (bars.length < period + 1) return null;\n let trSum = 0;\n for (let i = bars.length - period; i < bars.length; i++) {\n const tr = Math.max(\n highs[i] - lows[i],\n Math.abs(highs[i] - closes[i - 1]),\n Math.abs(lows[i] - closes[i - 1]),\n );\n trSum += tr;\n }\n return trSum / period;\n };\n // Stochastic\n const stoch = (period: number = 14) => {\n if (bars.length < period) return null;\n const slice = bars.slice(-period);\n const highestHigh = Math.max(...slice.map((b: any) => b.high));\n const lowestLow = Math.min(...slice.map((b: any) => b.low));\n const currentClose = closes[closes.length - 1];\n if (highestHigh === lowestLow) return { k: 50, d: 50 };\n const k = ((currentClose - lowestLow) / (highestHigh - lowestLow)) * 100;\n return { k, d: k * 0.9 };\n };\n // ADX (simplified)\n const adx = (period: number = 14) => {\n if (bars.length < period * 2) return null;\n let plusDM = 0, minusDM = 0, tr = 0;\n for (let i = bars.length - period; i < bars.length; i++) {\n const upMove = highs[i] - highs[i - 1];\n const downMove = lows[i - 1] - lows[i];\n if (upMove > downMove && upMove > 0) plusDM += upMove;\n if (downMove > upMove && downMove > 0) minusDM += downMove;\n tr += Math.max(highs[i] - lows[i], Math.abs(highs[i] - closes[i - 1]));\n }\n const di_plus = (plusDM / tr) * 100;\n const di_minus = (minusDM / tr) * 100;\n const dx = Math.abs(di_plus - di_minus) / (di_plus + di_minus) * 100;\n return dx;\n };\n\n return {\n symbol: ohlcv.symbol,\n timeframe,\n lastPrice: last,\n indicators: {\n sma: { sma20: sma(20), sma50: sma(50), sma200: sma(200) },\n ema: { ema12: ema(12), ema20: ema(20), ema50: ema(50), ema200: ema(200) },\n rsi: rsi(14),\n macd: macd(),\n bollinger: bollinger(20),\n atr: atr(14),\n stochastic: stoch(14),\n adx: adx(14),\n volume: volumes[volumes.length - 1],\n avgVolume20: volumes.slice(-20).reduce((a: number, b: number) => a + b, 0) / Math.min(20, volumes.length),\n },\n };\n } catch (e) {\n return { error: `Technicals failed: ${e.message}` };\n }\n}\n\n// ─── Tool: get_technicals_rating ─────────────────────────────────────\nexport async function getTechnicalsRating(symbol: string, timeframe: string = \"1D\"): Promise {\n const tech = await getTechnicals(symbol, timeframe);\n if (tech.error) return tech;\n\n const i = tech.indicators;\n let buySignals = 0;\n let sellSignals = 0;\n const breakdown: any[] = [];\n\n // RSI\n if (i.rsi != null) {\n if (i.rsi < 30) { buySignals++; breakdown.push({ indicator: \"RSI\", signal: \"BUY\", value: i.rsi }); }\n else if (i.rsi > 70) { sellSignals++; breakdown.push({ indicator: \"RSI\", signal: \"SELL\", value: i.rsi }); }\n else breakdown.push({ indicator: \"RSI\", signal: \"NEUTRAL\", value: i.rsi });\n }\n // MACD\n if (i.macd) {\n if (i.macd.histogram > 0) { buySignals++; breakdown.push({ indicator: \"MACD\", signal: \"BUY\", value: i.macd.histogram }); }\n else { sellSignals++; breakdown.push({ indicator: \"MACD\", signal: \"SELL\", value: i.macd.histogram }); }\n }\n // EMA\n if (i.ema.ema20 && i.ema.ema50) {\n if (i.ema.ema20 > i.ema.ema50) { buySignals++; breakdown.push({ indicator: \"EMA20/50\", signal: \"BUY\", value: i.ema.ema20 }); }\n else { sellSignals++; breakdown.push({ indicator: \"EMA20/50\", signal: \"SELL\", value: i.ema.ema20 }); }\n }\n // Price vs SMA200\n if (i.sma.sma200) {\n if (tech.lastPrice > i.sma.sma200) { buySignals++; breakdown.push({ indicator: \"Price vs SMA200\", signal: \"BUY\", value: i.sma.sma200 }); }\n else { sellSignals++; breakdown.push({ indicator: \"Price vs SMA200\", signal: \"SELL\", value: i.sma.sma200 }); }\n }\n // Stochastic\n if (i.stochastic) {\n if (i.stochastic.k < 20) { buySignals++; breakdown.push({ indicator: \"Stochastic\", signal: \"BUY\", value: i.stochastic.k }); }\n else if (i.stochastic.k > 80) { sellSignals++; breakdown.push({ indicator: \"Stochastic\", signal: \"SELL\", value: i.stochastic.k }); }\n else breakdown.push({ indicator: \"Stochastic\", signal: \"NEUTRAL\", value: i.stochastic.k });\n }\n\n const total = buySignals + sellSignals;\n const rating = buySignals > sellSignals ? \"BUY\" : sellSignals > buySignals ? \"SELL\" : \"NEUTRAL\";\n const score = total > 0 ? Math.round((buySignals / total) * 100) : 50;\n\n return {\n symbol: tech.symbol,\n timeframe,\n rating,\n score,\n buySignals,\n sellSignals,\n breakdown,\n };\n}\n\n// ─── Tool: analyze_multi_timeframe ───────────────────────────────────\nexport async function analyzeMultiTimeframe(symbol: string): Promise {\n const timeframes = [\"15m\", \"1H\", \"4H\", \"1D\"];\n const results = await Promise.all(\n timeframes.map(async (tf) => {\n const rating = await getTechnicalsRating(symbol, tf);\n return { timeframe: tf, ...rating };\n }),\n );\n\n const validResults = results.filter((r) => !r.error);\n const buyCount = validResults.filter((r) => r.rating === \"BUY\").length;\n const sellCount = validResults.filter((r) => r.rating === \"SELL\").length;\n\n const alignmentScore = validResults.length > 0\n ? Math.round((Math.max(buyCount, sellCount) / validResults.length) * 100)\n : 0;\n\n const bias = buyCount > sellCount ? \"BULLISH\" : sellCount > buyCount ? \"BEARISH\" : \"MIXED\";\n\n return {\n symbol,\n bias,\n alignmentScore,\n buyCount,\n sellCount,\n timeframeDetails: validResults.map((r) => ({\n timeframe: r.timeframe,\n rating: r.rating,\n score: r.score,\n })),\n };\n}\n\n// ─── Tool: compute_levels ────────────────────────────────────────────\nexport async function computeLevels(symbol: string, timeframe: string = \"1D\"): Promise {\n const ohlcv = await getOHLCV(symbol, timeframe, 100);\n if (ohlcv.error) return ohlcv;\n const bars = ohlcv.bars;\n if (bars.length < 10) return { error: \"Not enough data for levels\" };\n\n // Swing highs and lows (lookback of 5 bars)\n const swingHighs: any[] = [];\n const swingLows: any[] = [];\n const lookback = 5;\n for (let i = lookback; i < bars.length - lookback; i++) {\n const isSwingHigh = bars.slice(i - lookback, i + lookback + 1).every(\n (b: any, idx: number) => idx === lookback || b.high <= bars[i].high,\n );\n const isSwingLow = bars.slice(i - lookback, i + lookback + 1).every(\n (b: any, idx: number) => idx === lookback || b.low >= bars[i].low,\n );\n if (isSwingHigh) swingHighs.push({ index: i, price: bars[i].high, timestamp: bars[i].timestamp });\n if (isSwingLow) swingLows.push({ index: i, price: bars[i].low, timestamp: bars[i].timestamp });\n }\n\n const lastPrice = bars[bars.length - 1].close;\n const resistanceLevels = swingHighs.slice(-5).map((s) => s.price);\n const supportLevels = swingLows.slice(-5).map((s) => s.price);\n\n // Recent range for premium/discount\n const recentBars = bars.slice(-50);\n const rangeHigh = Math.max(...recentBars.map((b: any) => b.high));\n const rangeLow = Math.min(...recentBars.map((b: any) => b.low));\n const range = rangeHigh - rangeLow;\n const fib50 = rangeLow + range * 0.5;\n const equilibrium = lastPrice > fib50 ? \"PREMIUM\" : \"DISCOUNT\";\n\n // FVG detection (simplified)\n const fvgs: any[] = [];\n for (let i = 2; i < bars.length; i++) {\n const gap = bars[i].low - bars[i - 2].high;\n if (gap > 0) {\n fvgs.push({ index: i, top: bars[i].low, bottom: bars[i - 2].high });\n }\n }\n\n return {\n symbol: ohlcv.symbol,\n timeframe,\n lastPrice,\n supportLevels,\n resistanceLevels,\n swingHighs: swingHighs.slice(-5).map((s) => ({ price: s.price, timestamp: s.timestamp })),\n swingLows: swingLows.slice(-5).map((s) => ({ price: s.price, timestamp: s.timestamp })),\n range: { high: rangeHigh, low: rangeLow, fib50, equilibrium },\n fairValueGaps: fvgs.slice(-3),\n };\n}\n\n// ─── Tool: get_news ──────────────────────────────────────────────────\nexport async function getNews(symbol: string): Promise {\n try {\n const res = await fetch(\n `${YF_BASE}/search?q=${encodeURIComponent(normalizeSymbol(symbol))}"esCount=0&newsCount=5`,\n { headers: { \"User-Agent\": \"Mozilla/5.0\" } },\n );\n const data = await res.json();\n return (data.news || []).map((n: any) => ({\n title: n.title,\n publisher: n.publisher,\n url: n.link,\n publishedAt: new Date(n.providerPublishTime * 1000).toISOString(),\n type: n.type,\n }));\n } catch (e) {\n return { error: `News failed: ${e.message}` };\n }\n}\n\n// ─── Tool: run_screener (simplified) ─────────────────────────────────\nexport async function runScreener(symbols: string[], condition: string): Promise {\n const results = await Promise.all(\n symbols.map(async (sym) => {\n const tech = await getTechnicals(sym, \"1D\");\n if (tech.error) return { symbol: sym, error: tech.error };\n return {\n symbol: sym,\n lastPrice: tech.lastPrice,\n rsi: tech.indicators.rsi,\n ema20: tech.indicators.ema.ema20,\n ema50: tech.indicators.ema.ema50,\n sma200: tech.indicators.sma.sma200,\n macdHistogram: tech.indicators.macd?.histogram,\n adx: tech.indicators.adx,\n };\n }),\n );\n\n // Simple condition matching\n return results.filter((r) => {\n if (r.error) return false;\n const lower = condition.toLowerCase();\n if (lower.includes(\"rsi > 50\")) return r.rsi != null && r.rsi > 50;\n if (lower.includes(\"rsi < 30\")) return r.rsi != null && r.rsi < 30;\n if (lower.includes(\"rsi > 70\")) return r.rsi != null && r.rsi > 70;\n if (lower.includes(\"close above ema200\") || lower.includes(\"close > ema200\")) {\n return r.sma200 != null && r.lastPrice > r.sma200;\n }\n if (lower.includes(\"ema20 > ema50\")) return r.ema20 != null && r.ema50 != null && r.ema20 > r.ema50;\n if (lower.includes(\"adx > 20\")) return r.adx != null && r.adx > 20;\n return true; // no filter → return all\n });\n}\n\n// ─── Tool: compare_symbols ───────────────────────────────────────────\nexport async function compareSymbols(symbols: string[]): Promise {\n const quotes = await getQuotesBatch(symbols);\n const technicals = await Promise.all(\n symbols.map((s) => getTechnicalsRating(s, \"1D\")),\n );\n return symbols.map((sym, i) => ({\n symbol: sym,\n quote: quotes[i],\n rating: technicals[i].rating,\n score: technicals[i].score,\n }));\n}\n\n// ─── Tool: calculate_correlation ─────────────────────────────────────\nexport async function calculateCorrelation(symbols: string[], timeframe: string = \"1D\"): Promise {\n const ohlcvData = await Promise.all(\n symbols.map((s) => getOHLCV(s, timeframe, 60)),\n );\n\n const logReturns: Record = {};\n symbols.forEach((sym, i) => {\n const data = ohlcvData[i];\n if (data.error) return;\n const closes = data.bars.map((b: any) => b.close);\n const returns: number[] = [];\n for (let j = 1; j < closes.length; j++) {\n returns.push(Math.log(closes[j] / closes[j - 1]));\n }\n logReturns[sym] = returns;\n });\n\n const matrix: Record> = {};\n for (const s1 of symbols) {\n matrix[s1] = {};\n for (const s2 of symbols) {\n const r1 = logReturns[s1];\n const r2 = logReturns[s2];\n if (!r1 || !r2) { matrix[s1][s2] = null; continue; }\n const minLen = Math.min(r1.length, r2.length);\n const mean1 = r1.slice(0, minLen).reduce((a: number, b: number) => a + b, 0) / minLen;\n const mean2 = r2.slice(0, minLen).reduce((a: number, b: number) => a + b, 0) / minLen;\n let cov = 0, var1 = 0, var2 = 0;\n for (let j = 0; j < minLen; j++) {\n const d1 = r1[j] - mean1;\n const d2 = r2[j] - mean2;\n cov += d1 * d2;\n var1 += d1 * d1;\n var2 += d2 * d2;\n }\n matrix[s1][s2] = (var1 > 0 && var2 > 0) ? cov / Math.sqrt(var1 * var2) : 0;\n }\n }\n return { symbols, timeframe, correlationMatrix: matrix };\n}\n","createdAt",["D",1785307518151],"branchVersion","branchId","7f4fd07b-175a-4243-9d9e-b81c40f32513","id","a9d8b9e9-d031-4c55-a731-b847098d7926","atn-cnos-bot",["D",1785307366530],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","Agentic Trading Network bot with CNOS cognitive resolution 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{ sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\n// ─── Schema Initialization ───────────────────────────────────────────\nexport async function initDB() {\n await sqlite.batch([\n {\n sql: `CREATE TABLE IF NOT EXISTS observations (\n id TEXT PRIMARY KEY,\n desk_id TEXT NOT NULL,\n agent_type TEXT NOT NULL,\n symbol TEXT NOT NULL,\n timeframe TEXT NOT NULL,\n observation_type TEXT NOT NULL,\n data_payload TEXT NOT NULL,\n confidence INTEGER DEFAULT 50,\n privacy_class TEXT DEFAULT 'shared',\n provenance TEXT,\n created_at TEXT DEFAULT (datetime('now'))\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS market_cases (\n id TEXT PRIMARY KEY,\n vertical TEXT DEFAULT 'ATN',\n domain TEXT DEFAULT 'trading',\n symbol TEXT NOT NULL,\n timeframe TEXT NOT NULL,\n hypothesis TEXT NOT NULL,\n expected_outcome TEXT,\n reasoning TEXT,\n invalidation_level TEXT,\n conviction INTEGER DEFAULT 50,\n time_horizon TEXT,\n meta_tags TEXT,\n evidence TEXT,\n resolution TEXT DEFAULT 'PENDING',\n resolution_reason TEXT,\n contradictions_resolved INTEGER DEFAULT 0,\n reuse_count INTEGER DEFAULT 0,\n contributors TEXT,\n confidence_history TEXT,\n outcome_hit_target INTEGER,\n outcome_rr_ratio REAL,\n follow_up_case TEXT,\n proof_artifact TEXT,\n created_at TEXT DEFAULT (datetime('now')),\n resolved_at TEXT\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS contradictions (\n id TEXT PRIMARY KEY,\n case_id TEXT NOT NULL,\n challenging_case_id TEXT,\n challenging_desk_id TEXT,\n contradiction_text TEXT NOT NULL,\n status TEXT DEFAULT 'OPEN',\n created_at TEXT DEFAULT (datetime('now')),\n resolved_at TEXT\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS resolved_memory (\n id TEXT PRIMARY KEY,\n case_id TEXT NOT NULL UNIQUE,\n embedding_key TEXT,\n reuse_count INTEGER DEFAULT 0,\n created_at TEXT DEFAULT (datetime('now'))\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS desks (\n id TEXT PRIMARY KEY,\n handle TEXT,\n agents_config TEXT,\n reputation INTEGER DEFAULT 100,\n contributions INTEGER DEFAULT 0,\n resolutions_correct INTEGER DEFAULT 0,\n resolutions_wrong INTEGER DEFAULT 0,\n created_at TEXT DEFAULT (datetime('now')),\n last_active TEXT\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS pipeline_runs (\n id TEXT PRIMARY KEY,\n stage TEXT NOT NULL,\n status TEXT NOT NULL,\n details TEXT,\n cases_processed INTEGER DEFAULT 0,\n created_at TEXT DEFAULT (datetime('now'))\n )`,\n },\n {\n sql: `CREATE INDEX IF NOT EXISTS idx_observations_symbol ON observations(symbol)`,\n },\n {\n sql: `CREATE INDEX IF NOT EXISTS idx_cases_symbol ON market_cases(symbol)`,\n },\n {\n sql: `CREATE INDEX IF NOT EXISTS idx_cases_resolution ON market_cases(resolution)`,\n },\n {\n sql: `CREATE INDEX IF NOT EXISTS idx_contradictions_case ON contradictions(case_id)`,\n },\n ]);\n}\n\n// ─── Helpers ─────────────────────────────────────────────────────────\nexport function uuid(): string {\n return crypto.randomUUID();\n}\n\nexport async function createObservation(obs: {\n desk_id: string;\n agent_type: string;\n symbol: string;\n timeframe: string;\n observation_type: string;\n data_payload: any;\n confidence?: number;\n privacy_class?: string;\n provenance?: string;\n}) {\n const id = uuid();\n await sqlite.execute({\n sql: `INSERT INTO observations (id, desk_id, agent_type, symbol, timeframe, observation_type, data_payload, confidence, privacy_class, provenance)\n VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)`,\n args: [\n id,\n obs.desk_id,\n obs.agent_type,\n obs.symbol,\n obs.timeframe,\n obs.observation_type,\n JSON.stringify(obs.data_payload),\n obs.confidence ?? 50,\n obs.privacy_class ?? \"shared\",\n obs.provenance ?? null,\n ],\n });\n return id;\n}\n\nexport async function createMarketCase(c: {\n desk_id: string;\n symbol: string;\n timeframe: string;\n hypothesis: string;\n expected_outcome?: string;\n reasoning?: string;\n invalidation_level?: string;\n conviction?: number;\n time_horizon?: string;\n meta_tags?: string[];\n evidence?: string[];\n proof_artifact?: string;\n}) {\n const id = uuid();\n const contributors = JSON.stringify([c.desk_id]);\n const confidence_history = JSON.stringify([\n { timestamp: new Date().toISOString(), score: c.conviction ?? 50, source: \"initial\" },\n ]);\n await sqlite.execute({\n sql: `INSERT INTO market_cases (id, symbol, timeframe, hypothesis, expected_outcome, reasoning,\n invalidation_level, conviction, time_horizon, meta_tags, evidence, contributors,\n confidence_history, proof_artifact)\n VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)`,\n args: [\n id,\n c.symbol,\n c.timeframe,\n c.hypothesis,\n c.expected_outcome ?? null,\n c.reasoning ?? null,\n c.invalidation_level ?? null,\n c.conviction ?? 50,\n c.time_horizon ?? null,\n c.meta_tags ? JSON.stringify(c.meta_tags) : null,\n c.evidence ? JSON.stringify(c.evidence) : null,\n contributors,\n confidence_history,\n c.proof_artifact ?? null,\n ],\n });\n return id;\n}\n\nexport async function updateCaseResolution(\n caseId: string,\n resolution: string,\n reason: string,\n) {\n await sqlite.execute({\n sql: `UPDATE market_cases SET resolution = ?, resolution_reason = ?, resolved_at = datetime('now')\n WHERE id = ?`,\n args: [resolution, reason, caseId],\n });\n if (resolution === \"CONFIRMED\" || resolution === \"REJECTED\") {\n await sqlite.execute({\n sql: `INSERT OR REPLACE INTO resolved_memory (id, case_id, embedding_key)\n VALUES (?, ?, ?)`,\n args: [uuid(), caseId, `embed_${caseId}`],\n });\n }\n}\n\nexport async function addContradiction(\n caseId: string,\n challengingDeskId: string,\n text: string,\n challengingCaseId?: string,\n) {\n const id = uuid();\n await sqlite.execute({\n sql: `INSERT INTO contradictions (id, case_id, challenging_case_id, challenging_desk_id, contradiction_text)\n VALUES (?, ?, ?, ?, ?)`,\n args: [id, caseId, challengingCaseId ?? null, challengingDeskId, text],\n });\n await sqlite.execute({\n sql: `UPDATE market_cases SET contradictions_resolved = contradictions_resolved + 1 WHERE id = ?`,\n args: [caseId],\n });\n return id;\n}\n\nexport async function incrementReuse(caseId: string) {\n await sqlite.execute({\n sql: `UPDATE market_cases SET reuse_count = reuse_count + 1 WHERE id = ?`,\n args: [caseId],\n });\n await sqlite.execute({\n sql: `UPDATE resolved_memory SET reuse_count = reuse_count + 1 WHERE case_id = ?`,\n args: [caseId],\n });\n}\n\nexport async function getStats() {\n const [members, agents, cases, memoryObjects, observations, confirmed, rejected, pending] =\n await Promise.all([\n sqlite.execute(\"SELECT COUNT(*) as c FROM desks\"),\n sqlite.execute(\"SELECT COUNT(DISTINCT agent_type) as c FROM observations\"),\n sqlite.execute(\"SELECT COUNT(*) as c FROM market_cases\"),\n sqlite.execute(\"SELECT COUNT(*) as c FROM resolved_memory\"),\n sqlite.execute(\"SELECT COUNT(*) as c FROM observations\"),\n sqlite.execute(\"SELECT COUNT(*) as c FROM market_cases WHERE resolution = 'CONFIRMED'\"),\n sqlite.execute(\"SELECT COUNT(*) as c FROM market_cases WHERE resolution = 'REJECTED'\"),\n sqlite.execute(\"SELECT COUNT(*) as c FROM market_cases WHERE resolution = 'PENDING'\"),\n ]);\n return {\n members: (members.rows[0] as any)?.c ?? 0,\n agents: Math.max((agents.rows[0] as any)?.c ?? 0, 6),\n cases: (cases.rows[0] as any)?.c ?? 0,\n memoryObjects: (memoryObjects.rows[0] as any)?.c ?? 0,\n observations: (observations.rows[0] as any)?.c ?? 0,\n confirmed: (confirmed.rows[0] as any)?.c ?? 0,\n rejected: (rejected.rows[0] as any)?.c ?? 0,\n pending: (pending.rows[0] as any)?.c ?? 0,\n };\n}\n\nexport async function logPipelineRun(stage: string, status: string, details: string, casesProcessed: number) {\n await sqlite.execute({\n sql: `INSERT INTO pipeline_runs (id, stage, status, details, cases_processed)\n VALUES (?, ?, ?, ?, ?)`,\n args: [uuid(), stage, status, details, casesProcessed],\n });\n}\n\nexport async function getRecentCases(limit: number = 10) {\n const result = await sqlite.execute({\n sql: `SELECT * FROM market_cases ORDER BY created_at DESC LIMIT ?`,\n args: [limit],\n });\n return result.rows.map((r) => ({\n ...r,\n meta_tags: r.meta_tags ? JSON.parse(r.meta_tags as string) : [],\n contributors: r.contributors ? JSON.parse(r.contributors as string) : [],\n })) as any[];\n}\n\nexport async function getRecentPipelineRuns(limit: number = 20) {\n const result = await sqlite.execute({\n sql: `SELECT * FROM pipeline_runs ORDER BY created_at DESC LIMIT ?`,\n args: [limit],\n });\n return result.rows as any[];\n}\n\nexport async function getCasesByResolution(resolution: string) {\n const result = await sqlite.execute({\n sql: `SELECT * FROM market_cases WHERE resolution = ? ORDER BY created_at DESC`,\n args: [resolution],\n });\n return result.rows.map((r) => ({\n ...r,\n meta_tags: r.meta_tags ? JSON.parse(r.meta_tags as string) : [],\n contributors: r.contributors ? JSON.parse(r.contributors as string) : [],\n })) as any[];\n}\n\nexport async function searchMemory(query: string, limit: number = 5) {\n const result = await sqlite.execute({\n sql: `SELECT mc.*, rm.reuse_count as memory_reuse\n FROM market_cases mc\n JOIN resolved_memory rm ON rm.case_id = mc.id\n WHERE mc.resolution IN ('CONFIRMED', 'REJECTED')\n AND (mc.hypothesis LIKE ? OR mc.symbol LIKE ? OR mc.meta_tags LIKE ?)\n ORDER BY rm.reuse_count DESC, mc.created_at DESC\n LIMIT ?`,\n args: [`%${query}%`, `%${query}%`, `%${query}%`, limit],\n });\n return result.rows.map((r) => ({\n ...r,\n meta_tags: r.meta_tags ? JSON.parse(r.meta_tags as string) : [],\n })) as any[];\n}\n",[],[138,166],["D",1785307426186],[158,159],[138],["D",1785307366530],["D",1789476648181],{"_105":104,"_113":109},{"_105":104,"_106":107,"_108":109,"_19":60,"_110":111,"_112":30},{"_13":94,"_37":95,"_48":47,"_96":49,"_97":-5,"_98":-5,"_99":-5,"_100":-5,"_101":-5,"_102":50,"_103":104},"ctx",{"_87":-5,"_133":213,"_214":215,"_216":217,"_218":30,"_219":30,"_220":30,"_221":64,"_222":-5,"_223":-7,"_224":-7,"_225":68,"_226":30,"_227":30,"_228":-5,"_229":30,"_230":30,"_231":30,"_232":-5},"ENV",{"_184":185,"_186":187,"_188":95,"_189":190,"_191":192,"_193":194,"_195":196,"_197":198,"_199":200,"_201":202,"_203":204,"_205":206,"_207":208,"_209":210,"_211":212},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

Diff · v2