Building a High-Quality Stock Report Generator with Node.js, Express, and OpenAI API

mkdir stock-report-generator
cd stock-report-generator
npm init -y

npm install express axios

mkdir routes utils data
touch app.js routes/report.js utils/helpers.js

// app.js
const express = require('express');
const reportRouter = require('./routes/report');

const app = express();

app.use(express.json());
app.use('/api', reportRouter);

const PORT = process.env.PORT || 3000;

app.listen(PORT, () => {
  console.log(`Server is running on port ${PORT}`);
});

// utils/helpers.js
const axios = require('axios');
const fs = require('fs');
const path = require('path');

const BASE_URL = 'https://your-data-api.com'; // Replace with your actual data API

/**
 * Get the start and end dates for the last year.
 * @returns {object} - An object containing `start` and `end` dates.
 */
function getLastYearDates() {
  const now = new Date();
  const end = now.toISOString().split('T')[0];
  now.setFullYear(now.getFullYear() - 1);
  const start = now.toISOString().split('T')[0];
  return { start, end };
}

/**
 * Convert an object to a string, excluding specified keys.
 * @param {object} obj - The object to convert.
 * @param {string[]} excludeKeys - Keys to exclude.
 * @returns {string} - The resulting string.
 */
function objectToString(obj, excludeKeys = []) {
  return Object.entries(obj)
    .filter(([key]) => !excludeKeys.includes(key))
    .map(([key, value]) => `${key}: ${value}`)
    .join('\n');
}

/**
 * Fetch data from a specified endpoint with given parameters.
 * @param {string} endpoint - API endpoint.
 * @param {object} params - Query parameters.
 * @param {any} defaultValue - Default value if the request fails.
 * @returns {Promise<any>} - The fetched data or default value.
 */
async function fetchData(endpoint, params = {}, defaultValue = null) {
  try {
    const response = await axios.get(`${BASE_URL}${endpoint}`, { params });
    return response.data || defaultValue;
  } catch (error) {
    console.error(`Error fetching data from ${endpoint}:`, error.message);
    return defaultValue;
  }
}

/**
 * Read data from a local JSON file.
 * @param {string} fileName - Name of the JSON file.
 * @returns {any} - The parsed data.
 */
function readLocalJson(fileName) {
  const filePath = path.join(__dirname, '../data', fileName);
  const data = fs.readFileSync(filePath, 'utf-8');
  return JSON.parse(data);
}

module.exports = {
  fetchData,
  objectToString,
  getLastYearDates,
  readLocalJson,
};

// routes/report.js
const express = require('express');
const {
  fetchData,
  objectToString,
  getLastYearDates,
  readLocalJson,
} = require('../utils/helpers');

const router = express.Router();

/**
 * Fetches stock data including historical prices, financials, MDA, and main business info.
 * @param {string} ticker - Stock ticker symbol.
 * @returns {Promise<object>} - An object containing all fetched data.
 */
async function fetchStockData(ticker) {
  try {
    const dates = getLastYearDates();
    const [historicalData, financialData, mdaData, businessData] = await Promise.all([
      fetchData('/stock_zh_a_hist', {
        symbol: ticker,
        period: 'weekly',
        start_date: dates.start,
        end_date: dates.end,
      }, []),

      fetchData('/stock_financial_benefit_ths', {
        code: ticker,
        indicator: '按年度',
      }, [{}]),

      fetchData('/stock_mda', { code: ticker }, []),

      fetchData('/stock_main_business', { code: ticker }, []),
    ]);

    const hist = historicalData[historicalData.length - 1];
    const currentPrice = (hist ? hist['开盘'] : 'N/A') + ' CNY';
    const historical = historicalData
      .map((item) => objectToString(item, ['股票代码']))
      .join('\n----------\n');

    const zsfzJson = readLocalJson('zcfz.json');
    const balanceSheet = objectToString(zsfzJson.find((item) => item['股票代码'] === ticker));

    const financial = objectToString(financialData[0]);

    const mda = mdaData.map(item => `${item['报告期']}\n${item['内容']}`).join('\n-----------\n');

    const mainBusiness = businessData.map(item =>
      `主营业务: ${item['主营业务']}\n产品名称: ${item['产品名称']}\n产品类型: ${item['产品类型']}\n经营范围: ${item['经营范围']}`
    ).join('\n-----------\n');

    return { currentPrice, historical, balanceSheet, mda, mainBusiness, financial };
  } catch (error) {
    console.error('Error fetching stock data:', error.message);
    throw error;
  }
}

const axios = require('axios');

const OPENAI_API_KEY = 'your-openai-api-key'; // Replace with your OpenAI API key

/**
 * Interacts with the OpenAI API to get completion results.
 * @param {array} messages - Array of messages, including system prompts and user messages.
 * @returns {Promise<string>} - The AI's response.
 */
async function analyzeWithOpenAI(messages) {
  try {
    const headers = {
      'Authorization': `Bearer ${OPENAI_API_KEY}`,
      'Content-Type': 'application/json',
    };
    const requestData = {
      model: 'gpt-4',
      temperature: 0.3,
      messages: messages,
    };

    const response = await axios.post(
      'https://api.openai.com/v1/chat/completions',
      requestData,
      { headers }
    );
    return response.data.choices[0].message.content.trim();
  } catch (error) {
    console.error('Error fetching analysis from OpenAI:', error.message);
    throw error;
  }
}

/**
 * Performs sentiment analysis on news articles using the OpenAI API.
 * @param {string} ticker - Stock ticker symbol.
 * @returns {Promise<string>} - Sentiment analysis summary.
 */
async function performSentimentAnalysis(ticker) {
  const systemPrompt = `You are a sentiment analysis assistant. Analyze the sentiment of the given news articles for ${ticker} and provide a summary of the overall sentiment and any notable changes over time. Be measured and discerning. You are a skeptical investor.`;

  const tickerNewsResponse = await fetchData('/stock_news_specific', { code: ticker }, []);

  const newsText = tickerNewsResponse
    .map(item => `${item['文章来源']} Date: ${item['发布时间']}\n${item['新闻内容']}`)
    .join('\n----------\n');

  const messages = [
    { role: 'system', content: systemPrompt },
    {
      role: 'user',
      content: `News articles for ${ticker}:\n${newsText || 'N/A'}\n----\nProvide a summary of the overall sentiment and any notable changes over time.`,
    },
  ];

  return await analyzeWithOpenAI(messages);
}

/**
 * Analyzes industry information using the OpenAI API.
 * @param {string} industry - Industry name.
 * @returns {Promise<string>} - Industry analysis summary.
 */
async function analyzeIndustry(industry) {
  const industryNewsResponse = await fetchData('/stock_news_specific', { code: industry }, []);
  const industryNewsArticles = industryNewsResponse
    .map(item => `${item['文章来源']} Date: ${item['发布时间']}\n${item['新闻内容']}`)
    .join('\n----------\n');

  const systemPrompt = `You are an industry analysis assistant. Provide an analysis of the ${industry} industry, including trends, growth prospects, regulatory changes, and competitive landscape.

Consider the following recent news articles relevant to the ${industry} industry:
${industryNewsArticles || 'N/A'}

Be measured and discerning. Truly think about the positives and negatives of the industry. Be sure of your analysis. You are a skeptical investor.`;

  const messages = [
    { role: 'system', content: systemPrompt },
    {
      role: 'user',
      content: `Provide an analysis of the ${industry} industry, taking into account the recent news articles provided.`,
    },
  ];

  return await analyzeWithOpenAI(messages);
}

/**
 * Generates the final investment report.
 * @param {string} ticker - Stock ticker symbol.
 * @param {object} data - Collected data and analyses.
 * @returns {Promise<string>} - The final report.
 */
async function provideFinalAnalysis(ticker, data) {
  const {
    sentimentAnalysis,
    industryAnalysis,
    balanceSheet,
    mda,
    mainBusiness,
    financial,
    currentPrice,
    historical,
  } = data;

  const systemPrompt = `You are a financial analyst tasked with providing a comprehensive investment recommendation for the stock ${ticker}. Your analysis should utilize the available data and aim for a length of approximately 1500 to 3000 words. Focus on the following key aspects:

1. **Company Overview**: Provide a brief overview of the company, including its business model, core products/services, and market position. Refer to the provided main business data.

2. **Financial Performance**:
   - Analyze key financial metrics based on the available data, including the current price (${currentPrice}), historical data, financial data, and balance sheet.
   - Highlight any significant financial trends and changes.

3. **Management Discussion and Analysis (MDA)**:
   - Summarize the management's insights and future outlook based on the provided MDA data.

4. **Sentiment Analysis**:
   - Summarize public sentiment based on recent news articles.
   - Include insights into any significant events or announcements that could influence market perception.

5. **Industry Analysis**:
   - Outline current industry trends and major players based on the available industry data.
   - Identify any regulatory or technological factors affecting the industry.

6. **Macroeconomic Factors**:
   - Analyze relevant macroeconomic indicators that may impact the company's performance.

7. **Risks and Opportunities**:
   - Identify key risks facing the company, including market, operational, and regulatory risks.
   - Highlight potential growth opportunities and strategic initiatives.

8. **Investment Recommendation**:
   - Based on your analysis, provide a clear recommendation (buy, hold, or sell) for the stock.
   - Support your recommendation with a well-reasoned rationale, considering both positives and negatives.

Please write in a professional tone, using precise language and relevant financial terminology. Respond in Chinese.`;

  const userPrompt = `Ticker: ${ticker}\n
1. **Sentiment Analysis**:\n${sentimentAnalysis}\n
2. **Industry Analysis**:\n${industryAnalysis}\n
3. **Financial Data**:\nCurrent Price: ${currentPrice}\nHistorical Data: ${historical}\nBalance Sheet: ${balanceSheet}\nFinancial Data: ${financial}\n
4. **Management Discussion and Analysis (MDA)**:\n${mda}\n
5. **Main Business**:\n${mainBusiness}\n\n
Based on the provided data and analyses, please provide a comprehensive investment analysis and recommendation for ${ticker}. Ensure the report length is controlled between 1500 and 3000 words, ensuring clarity and conciseness in your arguments.`;

  const messages = [
    { role: 'system', content: systemPrompt },
    {
      role: 'user',
      content: userPrompt,
    },
  ];

  return await analyzeWithOpenAI(messages);
}

router.post('/generate-report', async (req, res) => {
  const { ticker } = req.body;

  if (!ticker) {
    return res.status(400).json({ error: 'Ticker symbol is required.' });
  }

  try {
    const dataJson = readLocalJson('stock.json');
    const stockInfo = dataJson.find((item) => item.symbol === ticker);

    if (!stockInfo) {
      return res.status(404).json({ error: 'Stock information not found.' });
    }

    const { industry } = stockInfo;

    // Fetch stock data
    const stockData = await fetchStockData(ticker);

    // Perform analyses
    const [sentimentAnalysis, industryAnalysis] = await Promise.all([
      performSentimentAnalysis(ticker),
      analyzeIndustry(industry || 'the industry'),
    ]);

    // Generate final report
    const finalAnalysis = await provideFinalAnalysis(ticker, {
      sentimentAnalysis,
      industryAnalysis,
      ...stockData,
    });

    res.json({ report: finalAnalysis });
  } catch (error) {
    console.error('Error generating report:', error.message);
    res.status(500).json({ error: 'Failed to generate report.' });
  }
});

module.exports = router;

node app.js

curl -X POST http://localhost:3000/api/generate-report \
  -H 'Content-Type: application/json' \
  -d '{"ticker": "AAPL"}'