{"repo": "askaralim/nba-stats-api", "files": {"services/openaiService.js": {"3c344400e2280bb0b6142ec4a254b6e3d993b81f": {"t": 1785768947.0557935, "n": 16276, "h": "cae0c3c274a4cc3e", "c": "/**\n * OpenAI Service for Game Summary Generation\n * Uses api2d for OpenAI API access\n * Two-step process: 1) Analyze data → JSON, 2) Generate summary from JSON\n */\n\nconst axios = require('axios');\nconst logger = require('../utils/logger');\n\nclass OpenAIService {\n  constructor() {\n    this.apiKey = process.env.OPENAI_API_KEY;\n    this.baseURL = process.env.OPENAI_BASE_URL || 'https://openai.api2d.net/v1';\n    this.model = process.env.GPT_MODEL || 'gpt-3.5-turbo';\n    this.maxTokens = parseInt(process.env.GPT_MAX_TOKENS || '500');\n    this.temperature = parseFloat(process.env.GPT_TEMPERATURE || '0.7');\n  }\n\n  /**\n   * Step 1: Analyze game data and return structured JSON\n   * @param {Object} gameFacts - Structured game facts\n   * @returns {Promise<Object>} Analysis JSON\n   */\n  async analyzeGameData(gameFacts) {\n    if (!this.apiKey) {\n      throw new Error('OpenAI API key not configured');\n    }\n\n    const prompt = this.buildAnalysisPrompt(gameFacts);\n\n    try {\n      const response = await axios.post(\n        `${this.baseURL}/chat/completions`,\n        {\n          model: this.model,\n          messages: [\n            {\n              role: 'system',\n              content: '你是一个比赛数据分析引擎，而不是解说员。'\n            },\n            {\n              role: 'user',\n              content: prompt\n            }\n          ],\n          temperature: 0.3, // Lower temperature for more deterministic analysis\n          max_tokens: 800,\n          response_format: { type: 'json_object' }\n        },\n        {\n          headers: {\n            'Authorization': `Bearer ${this.apiKey}`,\n            'Content-Type': 'application/json'\n          },\n          timeout: 30000\n        }\n      );\n\n      const content = response.data?.choices?.[0]?.message?.content?.trim();\n      if (!content) {\n        throw new Error('Empty response from OpenAI');\n      }\n\n      // Parse JSON response\n      const analysis = JSON.parse(content);\n      return analysis;\n    } catch (error) {\n      logger.error({ component: 'openai', task: 'analysis', responseData: error.response?.data, errorMessage: error.message }, 'OpenAI analysis error');\n      throw error;\n    }\n  }\n\n  /**\n   * Step 2: Generate summary text from analysis JSON\n   * @param {Object} analysis - Analysis JSON from step 1\n   * @returns {Promise<string>} Generated summary text\n   */\n  async generateSummaryFromAnalysis(analysis) {\n    if (!this.apiKey) {\n      throw new Error('OpenAI API key not configured');\n    }\n\n    const prompt = this.buildSummaryPrompt(analysis);\n\n    try {\n      const response = await axios.post(\n        `${this.baseURL}/chat/completions`,\n        {\n          model: this.model,\n          messages: [\n            {\n              role: 'system',\n              content: '你是一名数据型比赛解说员。'\n            },\n            {\n              role: 'user',\n              content: prompt\n            }\n          ],\n          temperature: this.temperature,\n          max_tokens: this.maxTokens\n        },\n        {\n          headers: {\n            'Authorization': `Bearer ${this.apiKey}`,\n            'Content-Type': 'application/json'\n          },\n          timeout: 30000\n        }\n      );\n\n      const summary = response.data?.choices?.[0]?.message?.content?.trim();\n      if (!summary) {\n        throw new Error('Empty response from OpenAI');\n      }\n\n      return summary;\n    } catch (error) {\n      logger.error({ component: 'openai', task: 'summary', responseData: error.response?.data, errorMessage: error.message }, 'OpenAI summary error');\n      throw error;\n    }\n  }\n\n  /**\n   * Generate game summary using two-step process\n   * @param {Object} gameFacts - Structured game facts\n   * @returns {Promise<string>} Generated summary text\n   */\n  async generateGameSummary(gameFacts) {\n    try {\n      // Step 1: Analyze data and get JSON\n      const analysis = await this.analyzeGameData(gameFacts);\n      \n      // Step 2: Generate summary from analysis\n      const summary = await this.generateSummaryFromAnalysis(analysis);\n      \n      return summary;\n    } catch (error) {\n      logger.error({ component: 'openai', task: 'twoStepSummary', errorMessage: error.message }, 'Two-step AI summary generation failed');\n      throw error;\n    }\n  }\n\n  /**\n   * Build Step 1 prompt: Data analysis\n   * @param {Object} gameFacts - Structured game facts\n   * @returns {string} Formatted prompt\n   */\n  buildAnalysisPrompt(gameFacts) {\n    const {\n      home_team,\n      away_team,\n      home_score,\n      away_score,\n      home_half,\n      away_half,\n      q1,\n      q2,\n      q3,\n      q4,\n      fg_home_made,\n      fg_home_attempted,\n      fg_home_percent,\n      fg_away_made,\n      fg_away_attempted,\n      fg_away_percent,\n      three_home_made,\n      three_home_attempted,\n      three_home_percent,\n      three_away_made,\n      three_away_attempted,\n      three_away_percent,\n      ft_home_made,\n      ft_home_attempted,\n      ft_home_percent,\n      ft_away_made,\n      ft_away_attempted,\n      ft_away_percent,\n      to_home,\n      to_away,\n      reb_home,\n      reb_home_offensive,\n      reb_home_defensive,\n      reb_away,\n      reb_away_offensive,\n      reb_away_defensive,\n      has_overtime,\n      overtime_periods,\n      largest_lead_home,\n      largest_lead_away,\n      foul_home,\n      foul_away,\n      points_in_paint_home,\n      points_in_paint_away,\n      fast_break_points_home,\n      fast_break_points_away,\n      turnover_points_home,\n      turnover_points_away,\n      halftime_leader,\n      winner,\n      top_scorer_home,\n      top_scorer_away,\n      top_points_home,\n      top_points_away,\n    } = gameFacts;\n\n    // Build overtime section if applicable\n    let overtimeSection = '';\n    if (has_overtime && overtime_periods && overtime_periods.length > 0) {\n      const otScores = overtime_periods.map(ot => `OT${ot.period}: ${ot.score}`).join('\\n  ');\n      overtimeSection = `- 加时赛比分：\\n  ${otScores}\\n`;\n    }\n\n    return `请根据以下比赛数据，进行严格的数据对比分析，并以 JSON 格式输出结果。\n\n【分析规则】\n1. 只能使用给定数据，禁止推断或补充\n2. 标记主队是否在以下方面占优：\n   - 篮板\n   - 失误（更少为占优）\n   - 投篮命中率\n   - 三分命中数\n3. 判断比赛走势：\n   - 上半场领先方\n   - 下半场净胜方\n   - 是否进入加时\n4. 判断是否存在\"明确胜因\"：\n   - 若仅有 1 项轻微优势，标记为\"胜负接近\"\n5. 不使用任何主观或修饰性语言\n\n【输出 JSON 结构】\n{\n  \"home\": \"GSW\",\n  \"away\": \"LAL\",\n  \"winner\": \"home/away\",\n  \"halftime_leader\": \"home/away/tie\",\n  \"overtime\": true/false,\n  \"advantages\": {\n    \"rebounds\": \"home/away/none\",\n    \"rebounds_home\": number,\n    \"rebounds_away\": number,\n    \"turnovers\": \"home/away/none\",\n    \"turnovers_home\": number,\n    \"turnovers_away\": number,\n    \"fg_home_made\": number,\n    \"fg_away_made\": number,\n    \"fg_home_attempted\": number,\n    \"fg_away_attempted\": number,\n    \"fg_home_percentage\": number,\n    \"fg_away_percentage\": number,\n    \"three_pt_home_made\": number,\n    \"three_pt_away_made\": number,\n    \"three_pt_home_attempted\": number,\n    \"three_pt_away_attempted\": number,\n    \"three_pt_home_percentage\": number,\n    \"three_pt_away_percentage\": number,\n    \"ft_home_made\": number,\n    \"ft_away_made\": number,\n    \"ft_home_attempted\": number,\n    \"ft_away_attempted\": number,\n    \"ft_home_percentage\": number,\n    \"ft_away_percentage\": number,\n    \"points_in_paint_home\": number,\n    \"points_in_paint_away\": number,\n    \"fast_break_points_home\": number,\n    \"fast_break_points_away\": number,\n    \"turnover_points_home\": number,\n    \"turnover_points_away\": number,\n    \"largest_lead_home\": number,\n    \"largest_lead_away\": number,\n    \"foul_home\": number,\n    \"foul_away\": number,\n    \"decisive_factors\": [decisive_factor1, decisive_factor2, ...],\n    \"close_game\": true/false\n  },\n  \"decisive_factors\": [decisive_factor1, decisive_factor2, ...],\n  \"close_game\": true/false\n}\n\n比赛数据：\n- 主队：${home_team}\n- 客队：${away_team}\n- 最终比分：${home_score} - ${away_score}\n- 半场比分：${home_half} - ${away_half}\n- 每节比分：\n  Q1: ${q1}\n  Q2: ${q2}\n  Q3: ${q3}\n  Q4: ${q4}\n${overtimeSection}\n- 投篮命中数（主）：${fg_home_made} 投篮出手数：${fg_home_attempted}\n- 投篮命中率（主）：${fg_home_percent}%\n- 投篮命中数（客）：${fg_away_made} 投篮出手数：${fg_away_attempted}\n- 投篮命中率（客）：${fg_away_percent}%\n- 三分命中数（主）：${three_home_made} 三分出手数：${three_home_attempted}\n- 三分命中率（主）：${three_home_percent}%\n- 三分命中数（客）：${three_away_made} 三分出手数：${three_away_attempted}\n- 三分命中率（客）：${three_away_percent}%\n- 罚球命中数（主）：${ft_home_made} 罚球出手数：${ft_home_attempted}\n- 罚球命中率（主）：${ft_home_percent}%\n- 罚球命中数（客）：${ft_away_made} 罚球出手数：${ft_away_attempted}\n- 罚球命中率（客）：${ft_away_percent}%\n- 失误（主/客）：${to_home} / ${to_away}\n- 篮板（主/客）：${reb_home} / ${reb_away}\n- 篮板（主/客）：${reb_home_offensive} / ${reb_away_offensive}\n- 篮板（主/客）：${reb_home_defensive} / ${reb_away_defensive}\n- 最大领先（主/客）：${largest_lead_home} / ${largest_lead_away}\n- 犯规（主/客）：${foul_home} / ${foul_away}\n- 内线得分（主/客）：${points_in_paint_home} / ${points_in_paint_away}\n- 快攻得分（主/客）：${fast_break_points_home} / ${fast_break_points_away}\n- 失误得分（主/客）：${turnover_points_home} / ${turnover_points_away}\n  `;}\n\n  /**\n   * Translate NBA news article to Simplified Chinese\n   * @param {Object} params - { title, content }\n   * @returns {Promise<{ translated_title: string, translated_content: string }>}\n   */\n  async translateNewsArticle({ title = '', content }) {\n    if (!this.apiKey) {\n      throw new Error('OpenAI API key not configured');\n    }\n    if (!content || typeof content !== 'string') {\n      throw new Error('Content is required for translation');\n    }\n\n    const noPromoLinksInstruction =\n    '\\n\\nImportant: Do not include promotional or tracking short links in your translation (e.g. nba.smart.link/…, other smart.link URLs, or bare app/watch CTAs that are only URLs). Remove them entirely from translated_title and translated_content. If the source ends with symbols like ➡️ or text that only points to such a link, end the Chinese sentence naturally without any URL.';\n    const userPrompt = title\n    ? `Translate the following NBA news to Simplified Chinese. Keep it professional, accurate, and fluent.${noPromoLinksInstruction}\\n\\nTitle: ${title}\\n\\nContent:\\n${content}\\n\\nRespond with JSON only: { \"translated_title\": \"...\", \"translated_content\": \"...\" }`\n    : `Translate the following NBA news to Simplified Chinese. Keep it professional, accurate, and fluent.${noPromoLinksInstruction}\\n\\nContent:\\n${content}\\n\\nRespond with JSON only: { \"translated_title\": \"...\", \"translated_content\": \"...\" }. Use the first sentence or a short summary as translated_title if no title is given.`;\n\n    try {\n      const response = await axios.post(\n        `${this.baseURL}/chat/completions`,\n        {\n          model: this.model,\n          messages: [\n            {\n              role: 'system',\n              content: '你是一个专业的体育新闻翻译。将英文NBA新闻翻译成简体中文，保持专业、准确、流畅。译文标题和正文中不要保留营销推广类短链接（例如 nba.smart.link/ 等）；删除这类链接及仅用于引流的符号（如 ➡️），必要时改写使语句通顺。只输出JSON，不要其他文字。'\n\n            },\n            {\n              role: 'user',\n              content: userPrompt\n            }\n          ],\n          temperature: 0.3,\n          max_tokens: 2000,\n          response_format: { type: 'json_object' }\n        },\n        {\n          headers: {\n            'Authorization': `Bearer ${this.apiKey}`,\n            'Content-Type': 'application/json'\n          },\n          timeout: 60000\n        }\n      );\n\n      const contentStr = response.data?.choices?.[0]?.message?.content?.trim();\n      if (!contentStr) {\n        throw new Error('Empty response from OpenAI');\n      }\n\n      const result = JSON.parse(contentStr);\n      return {\n        translated_title: result.translated_title || result.translatedTitle || '',\n        translated_content: result.translated_content || result.translatedContent || content\n      };\n    } catch (error) {\n      logger.error({ component: 'openai', task: 'translation', responseData: error.response?.data, errorMessage: error.message }, 'OpenAI translation error');\n      throw error;\n    }\n  }\n\n  /**\n   * Generate Swish Insight for a top performer (Chinese, data-driven)\n   * @param {Object} payload - { playerName, gameStats, seasonStats }\n   * @returns {Promise<string>} 1-2 sentence insight in Chinese\n   */\n  async generateSwishInsight(payload) {\n    if (!this.apiKey) {\n      throw new Error('OpenAI API key not configured');\n    }\n\n    const { playerName, gameStats = {}, seasonStats = {} } = payload;\n    const seasonData = seasonStats?.stats || seasonStats || {};\n    const gamePts = parseInt(gameStats.points) || 0;\n    const gameReb = parseInt(gameStats.rebounds) || 0;\n    const gameAst = parseInt(gameStats.assists) || 0;\n    const gameStl = parseInt(gameStats.steals) || 0;\n    const gameBlk = parseInt(gameStats.blocks) || 0;\n    const gameTov = parseInt(gameStats.turnovers) || 0;\n\n    const fg = (gameStats.fieldGoals || '0-0').split('-');\n    const three = (gameStats.threePointers || '0-0').split('-');\n    const ft = (gameStats.freeThrows || '0-0').split('-');\n    const fgm = parseInt(fg[0]) || 0;\n    const fga = parseInt(fg[1]) || 0;\n    const threePM = parseInt(three[0]) || 0;\n    const threePA = parseInt(three[1]) || 0;\n    const ftm = parseInt(ft[0]) || 0;\n    const fta = parseInt(ft[1]) || 0;\n\n    const fgPct = fga > 0 ? Math.round((fgm / fga) * 100) : 0;\n    const threePct = threePA > 0 ? Math.round((threePM / threePA) * 100) : 0;\n    const ftPct = fta > 0 ? Math.round((ftm / fta) * 100) : 0;\n\n    const seasonPts = parseFloat(seasonData.avgPoints || seasonData.points || 0) || 0;\n    const seasonFg = parseFloat(seasonData.fieldGoalPct || seasonData.fieldGoalPercentage || 0) || 0;\n    const seasonThree = parseFloat(seasonData.threePointFieldGoalPct || seasonData.threePointFieldGoalPercentage || 0) || 0;\n    const seasonFt = parseFloat(seasonData.freeThrowPct || seasonData.freeThrowPercentage || 0) || 0;\n    const seasonReb = parseFloat(seasonData.avgRebounds || seasonData.rebounds || 0) || 0;\n    const seasonAst = parseFloat(seasonData.avgAssists || seasonData.assists || 0) || 0;\n    const seasonStl = parseFloat(seasonData.avgSteals || seasonData.steals || 0) || 0;\n    const seasonBlk = parseFloat(seasonData.avgBlocks || seasonData.blocks || 0) || 0;\n    const seasonTov = parseFloat(seasonData.avgTurnovers || seasonData.turnovers || 0) || 0;\n\n    const userPrompt = `球员：${playerName}\n\n本场数据：${gamePts}分 ${gameReb}篮板 ${gameAst}助攻 ${gameStl}抢断 ${gameBlk}盖帽 ${gameTov}失误，投篮${fgm}/${fga}（${fgPct}%），三分${threePM}/${threePA}（${threePct}%），罚球${ftm}/${fta}（${ftPct}%）\n\n赛季场均：${seasonPts}分 ${seasonReb}篮板 ${seasonAst}助攻 ${seasonStl}抢断 ${seasonBlk}盖帽 ${seasonTov}失误，投篮${seasonFg}%，三分${seasonThree}%，罚球${seasonFt}%\n\n这是球员${playerName}的本场数据和赛季场均数据，请生成一句非常简短的数据洞察（最多20个汉字）。要求：\n- 突出球员对比赛的影响力\n- 球员对比赛的影响力包括进攻以及防守两个方面\n- 进攻球员需要在命中率以及得分上有显著的表现\n- 防守球员需要在抢断、篮板、盖帽以上有显著的表现\n- 如果球员有三双表现需要特别强调\n- 必须包含具体数字，不要解释背景\n- 按照你的理解，突出影响比赛的具体数据以及表现\n- 像体育解说的短评\n- 只输出一句话`;\n\n    try {\n      const response = await axios.post(\n        `${this.baseURL}/chat/completions`,\n        {\n          model: this.model,\n          messages: [\n            {\n              role: 'system',\n              content: '你是一个NBA数据分析师。根据本场数据和赛季场均数据，生成一句简短的数据洞察，用中文。不要空洞赞美，要有具体对比。只输出洞察文字，不要引号或前缀。'\n            },\n            {\n              role: 'user',\n              content: userPrompt\n            }\n          ],\n          temperature: 0.5,\n          max_tokens: 40\n        },\n        {\n          headers: {\n            'Authorization': `Bearer ${this.apiKey}`,\n            'Content-Type': 'application/json'\n          },\n          timeout: 15000\n        }\n      );\n\n      const insight = response.data?.choices?.[0]?.message?.content?.trim();\n      if (!insight) {\n        throw new Error('Empty response from OpenAI');\n      }\n      return insight;\n    } catch (error) {\n      logger.error({ component: 'openai', task: 'swishInsight', responseData: error.response?.data, errorMessage: error.message }, 'OpenAI Swish Insight error');\n      throw error;\n    }\n  }\n\n  /**\n   * Build Step 2 prompt: Generate summary from analysis\n   * @param {Object} analysis - Analysis JSON from step 1\n   * @returns {string} Formatted prompt\n   */\n  buildSummaryPrompt(analysis) {\n    const analysisJson = JSON.stringify(analysis, null, 2);\n\n    return `请严格根据以下分析结果，用中文总结比赛。\n\n【写作规则】\n1. 只能使用提供的分析结论，禁止自行推断\n2. 若 close_game 为 true，尽量分析比赛成败关键因素，如果无法分析则不用描述\n3. 只能将 decisive_factors 中的数据作为胜因\n4. 若有加时赛，只能描述加时比分差异，若没有则不用描述加时赛\n5. 禁止使用情绪化或主观词语\n6. 如果不能准确翻译球队名称，请使用球队英文名或简称。\n7. 字数 60–120 字\n8. 语言可以轻松，口语化，不要过于正式\n\n【分析结果】\n${analysisJson}`;\n  }\n}\n\nmodule.exports = new OpenAIService();\n"}}}}