Kazuma
74 lines
2.6 KiB
TypeScript
74 lines
2.6 KiB
TypeScript
import Anthropic from '@anthropic-ai/sdk';
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import type { Logger, LLMAnalysis } from '../types.js';
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interface Story {
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title: string;
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publisher?: string;
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}
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const SYSTEM_PROMPT = `You are a professional equity analyst. You will be given a list of today's market news headlines and the tickers already identified as catalysts.
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Your job is to:
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1. Write a 2-3 sentence market summary capturing the dominant theme
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2. Identify up to 4 industries that are likely to be secondarily affected (not directly mentioned but impacted by contagion, supply chain, regulation, or macro effects)
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3. Suggest up to 5 related ticker symbols worth screening that are NOT already in the provided list
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4. Assess overall market sentiment as BULLISH, NEUTRAL, or BEARISH based on the news
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Return ONLY valid JSON in this exact shape — no markdown, no explanation:
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{
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"summary": "string",
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"sentiment": "BULLISH" | "NEUTRAL" | "BEARISH",
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"affectedIndustries": [
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{ "name": "string", "reason": "string (one sentence)" }
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],
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"relatedTickers": [
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{ "ticker": "string", "reason": "string (one sentence)" }
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]
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}`;
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export class LLMAnalyst {
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private logger: Pick<Logger, 'log' | 'warn'>;
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private client: Anthropic | null;
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constructor({ logger }: { logger?: Pick<Logger, 'log' | 'warn'> } = {}) {
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this.logger = logger ?? { log: console.log, warn: console.warn };
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this.client = process.env.ANTHROPIC_API_KEY
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? new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY })
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: null;
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}
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async analyze(stories: Story[], existingTickers: string[] = []): Promise<LLMAnalysis | null> {
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if (!this.client) {
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this.logger.warn('LLMAnalyst: ANTHROPIC_API_KEY not set — skipping analysis');
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return null;
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}
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if (!stories?.length) return null;
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const headlines = stories
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.slice(0, 15)
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.map((s, i) => `${i + 1}. ${s.title} (${s.publisher ?? 'unknown'})`)
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.join('\n');
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const userMessage = `Today's market news headlines:\n\n${headlines}\n\nAlready identified catalyst tickers: ${existingTickers.join(', ') || 'none'}`;
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try {
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const response = await this.client.messages.create({
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model: 'claude-haiku-4-5',
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max_tokens: 1024,
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system: SYSTEM_PROMPT,
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messages: [{ role: 'user', content: userMessage }],
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});
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const raw = (response.content[0] as { text?: string })?.text ?? '';
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const cleaned = raw
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.replace(/^```(?:json)?\s*/i, '')
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.replace(/```\s*$/i, '')
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.trim();
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return JSON.parse(cleaned) as LLMAnalysis;
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} catch (err) {
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this.logger.warn('LLMAnalyst: analysis failed —', (err as Error).message);
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return null;
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}
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}
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}
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