Earnings Call Intelligence Briefing

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Fetching live market data... Calculating growth metrics... Synthesizing intelligence...

\n\n\n`;\n}\n\n// --- HONO ROUTER & MAIN HANDLER ---\nconst app = new Hono();\n\napp.use(\"*\", cors());\n\napp.get(\"/\", (c) => c.html(generateHtml(c.req.url)));\n\napp.post(\"/api/report\", async (c) => {\n try {\n const { ticker, call_date } = await c.req.json();\n if (!ticker) return c.json({ error: \"Ticker is required.\" }, 400);\n\n // Here we are using the `yahoo-finance2` library to fetch live data\n const [summaryData, newsData] = await Promise.all([\n yahooFinance.quoteSummary(ticker, {\n modules: [\"summaryProfile\", \"quoteType\", \"earningsHistory\", \"financialData\"],\n }),\n yahooFinance.search(ticker, { newsCount: 10 }),\n ]);\n\n const rawHistory = summaryData.earningsHistory?.history || [];\n const earningsAnalysis = analyzeEarningsHistory(rawHistory);\n\n // Structure the data for the AI\n const liveFinancialData = {\n companyProfile: {\n Name: summaryData.quoteType?.longName || summaryData.quoteType?.shortName || ticker,\n Symbol: summaryData.quoteType?.symbol || ticker,\n Description: summaryData.summaryProfile?.longBusinessSummary || \"No description available.\",\n Sector: summaryData.summaryProfile?.sector || \"N/A\",\n Industry: summaryData.summaryProfile?.industry || \"N/A\",\n },\n earningsAnalysis: earningsAnalysis,\n rawQuarterlyHistory: rawHistory.slice(0, 4).map(h => ({\n reportDate: h.quarter?.fmt || \"N/A\",\n epsActual: h.epsActual?.fmt || \"N/A\",\n revenueActual: h.revenue?.fmt || \"N/A\",\n })),\n newsHeadlines: newsData.news?.map(n => ({\n title: n.title,\n publisher: n.publisher,\n })) || [],\n };\n\n const userInput = `\n --- USER REQUEST ---\n Company Ticker: ${ticker}\n Upcoming Earnings Call Date: ${call_date}\n\n --- CONVICTION SCORE MODEL ---\n Use this exact formula:\n $$ S_c = \\\\alpha + \\\\beta_1(G_{rev}) + \\\\beta_2(M_{exp}) + \\\\beta_3(S_{news}) + \\\\epsilon $$\n Where:\n - $S_c$ = Conviction Score\n - $G_{rev}$ = Revenue Growth (QoQ)\n - $M_{exp}$ = Margin Expansion (bps)\n - $S_{news}$ = News Sentiment Score (-1 to 1), which you must infer.\n\n --- LIVE FINANCIAL DATA & ANALYSIS (from Yahoo Finance) ---\n ${JSON.stringify(liveFinancialData, null, 2)}\n `;\n\n const openai = new OpenAI();\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: EARNINGS_ANALYST_PROMPT_WITH_DATA },\n { role: \"user\", content: userInput },\n ],\n temperature: 0.1,\n });\n\n const report = completion.choices[0].message.content;\n return c.text(report);\n } catch (error) {\n console.error(\"Report Generation Error:\", error);\n return c.json({ error: error.message || \"An internal server error occurred.\" }, 500);\n }\n});\n\nexport default app.fetch;","deleted","label",[98],"permalink","https://www.val.town/x/join/rockstar/code/main.tsx","extension","actionData","errors"]