Stock Analyzer

Enter a stock ticker and optionally your API keys. If keys are omitted, the tool will attempt to use cached data (up to 1 day old).

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\n\n \n \n \n `);\n});\n\napp.post(\"/analyze\", async (c) => {\n try {\n const body = await c.req.json();\n const result = await runAnalysisPipeline(body);\n return c.json(result);\n } catch (error: any) {\n // Log the detailed error internally for debugging\n console.error(\"Analysis Pipeline Error:\", error);\n // Return a user-friendly error message\n return c.json({ error: error.message || \"An unexpected error occurred during analysis.\" }, 500);\n }\n});\n\n// --- Testing Stub ---\nexport async function runSelfTest() {\n console.log(\"Starting self-test...\");\n const testPayload: Input = {\n ticker: \"FAKE\", // Use a fake ticker that likely won't hit real APIs if keys are absent\n alphaVantageKey: \"FAKE_AV_KEY\", // Use fake keys\n polygonKey: \"FAKE_POLY_KEY\",\n };\n\n // Mock fetch to avoid actual API calls and simulate responses\n const originalFetch = global.fetch;\n global.fetch = (url: string, options?: any): Promise => {\n console.log(`Mock fetch called for: ${url}`);\n let responseData: any = {};\n let status = 200;\n\n if (url.includes(\"alphavantage\")) {\n // Provide minimal valid-looking structure for SMA/Volatility calculation\n responseData = {\n \"Meta Data\": { \"2. Symbol\": \"FAKE\" },\n \"Time Series (Daily)\": {\n \"2025-04-22\": { \"5. adjusted close\": \"155.00\" },\n \"2025-04-21\": { \"5. adjusted close\": \"154.00\" },\n // ... need at least 201 entries for 200-day calculations\n // Let's generate some fake data\n },\n };\n const startDate = new Date(\"2024-06-01\"); // Enough history\n for (let i = 0; i < 250; i++) {\n const date = new Date(startDate);\n date.setDate(startDate.getDate() + i);\n const dateString = date.toISOString().split(\"T\")[0];\n responseData[\"Time Series (Daily)\"][dateString] = {\n \"5. adjusted close\": (150 + Math.random() * 10).toFixed(2), // Random close price\n };\n }\n } else if (url.includes(\"polygon.io\")) {\n responseData = {\n ticker: \"FAKE\",\n status: \"OK\",\n results: [{ c: 155.50, t: Date.now() - 86400000 }], // Fake previous close\n count: 1,\n };\n } else {\n status = 404;\n responseData = { error: \"Mock endpoint not found\" };\n }\n\n return Promise.resolve({\n ok: status >= 200 && status < 300,\n status: status,\n statusText: status === 200 ? \"OK\" : \"Error\",\n json: () => Promise.resolve(responseData),\n text: () => Promise.resolve(JSON.stringify(responseData)), // For error handling in polygon fetch\n });\n };\n\n try {\n // Clear cache for the fake ticker before running the test\n await sqlite.execute({\n sql: `DELETE FROM api_cache WHERE key = ? OR key = ?`,\n args: [`alphavantage_${testPayload.ticker}`, `polygon_${testPayload.ticker}`],\n });\n console.log(`Cleared cache for ${testPayload.ticker}`);\n\n const result = await runAnalysisPipeline(testPayload);\n\n // Check if the pipeline reached the report generation step\n if (result.log.some(step => step.includes(\"Generating report\"))) {\n console.log(\"Self-test OK\");\n // console.log(\"Test Report:\\n\", result.report); // Optional: print report\n // console.log(\"Test Log:\\n\", result.log); // Optional: print log\n } else {\n console.error(\"Self-test FAILED: Did not reach report generation step.\");\n console.error(\"Test Log:\\n\", result.log);\n }\n } catch (error) {\n console.error(\"Self-test FAILED with error:\", error);\n } finally {\n // Restore original fetch\n global.fetch = originalFetch;\n console.log(\"Self-test finished.\");\n }\n}\n\n// Export the Hono app for serving\nexport default serve(app);\n\n// Example of how to run the self-test (e.g., in Val Town console or another Val)\n// await runSelfTest();","deleted","label",[98],"permalink","https://www.val.town/x/salon/test/code/main.tsx","extension","actionData","errors"]