mirror of
https://github.com/ArvinLovegood/go-stock.git
synced 2025-07-19 00:00:09 +08:00
7b93d4d8ca
感谢 @gnim2600 的建议！ - 新增 AIResponseResult 模型用于保存 AI 分析结果 - 实现 SaveAIResponseResult 和 GetAIResponseResult 函数 - 在前端添加 AI 分析功能，包括保存和获取分析结果 -优化 AI 分析界面，增加分析时间显示和再次分析按钮
468 lines
15 KiB
Go
468 lines
15 KiB
Go
package data
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import (
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"bufio"
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"context"
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"encoding/json"
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"fmt"
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"github.com/PuerkitoBio/goquery"
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"github.com/chromedp/chromedp"
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"github.com/duke-git/lancet/v2/strutil"
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"github.com/go-resty/resty/v2"
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"go-stock/backend/db"
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"go-stock/backend/logger"
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"go-stock/backend/models"
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"strings"
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"sync"
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"time"
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)
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// @Author spark
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// @Date 2025/1/16 13:19
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// @Desc
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// -----------------------------------------------------------------------------------
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type OpenAi struct {
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BaseUrl string `json:"base_url"`
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ApiKey string `json:"api_key"`
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Model string `json:"model"`
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MaxTokens int `json:"max_tokens"`
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Temperature float64 `json:"temperature"`
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Prompt string `json:"prompt"`
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TimeOut int `json:"time_out"`
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}
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func NewDeepSeekOpenAi() *OpenAi {
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config := getConfig()
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return &OpenAi{
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BaseUrl: config.OpenAiBaseUrl,
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ApiKey: config.OpenAiApiKey,
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Model: config.OpenAiModelName,
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MaxTokens: config.OpenAiMaxTokens,
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Temperature: config.OpenAiTemperature,
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Prompt: config.Prompt,
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TimeOut: config.OpenAiApiTimeOut,
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}
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}
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type THSTokenResponse struct {
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Code int `json:"code"`
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Message string `json:"message"`
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Data string `json:"data"`
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}
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type AiResponse struct {
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Id string `json:"id"`
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Object string `json:"object"`
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Created int `json:"created"`
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Model string `json:"model"`
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Choices []struct {
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Index int `json:"index"`
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Message struct {
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Role string `json:"role"`
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Content string `json:"content"`
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} `json:"message"`
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Logprobs interface{} `json:"logprobs"`
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FinishReason string `json:"finish_reason"`
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} `json:"choices"`
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Usage struct {
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PromptTokens int `json:"prompt_tokens"`
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CompletionTokens int `json:"completion_tokens"`
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TotalTokens int `json:"total_tokens"`
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PromptCacheHitTokens int `json:"prompt_cache_hit_tokens"`
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PromptCacheMissTokens int `json:"prompt_cache_miss_tokens"`
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} `json:"usage"`
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SystemFingerprint string `json:"system_fingerprint"`
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}
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func (o OpenAi) NewChat(stock string) string {
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client := resty.New()
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client.SetBaseURL(o.BaseUrl)
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client.SetHeader("Authorization", "Bearer "+o.ApiKey)
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client.SetHeader("Content-Type", "application/json")
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res := &AiResponse{}
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_, err := client.R().
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SetResult(res).
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SetBody(map[string]interface{}{
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"model": o.Model,
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"max_tokens": o.MaxTokens,
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"temperature": o.Temperature,
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"messages": []map[string]interface{}{
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{
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"role": "system",
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"content": "作为一位专业的A股市场分析师和投资顾问,请你根据以下信息提供详细的技术分析和投资策略建议:" +
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"1. 市场背景:\n" +
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"- 当前A股市场整体走势(如:牛市、熊市、震荡市)\n " +
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"- 近期影响市场的主要宏观经济因素\n " +
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"- 市场情绪指标(如:融资融券余额、成交量变化) " +
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"2. 技术指标分析: " +
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"- 当前股价水平" +
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"- 所在boll区间" +
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"- 上证指数的MA(移动平均线)、MACD、KDJ指标分析\n " +
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"- 行业板块轮动情况\n " +
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"- 近期市场热点和龙头股票的技术形态 " +
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"3. 风险评估:\n " +
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"- 当前市场主要风险因素\n " +
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"- 如何设置止损和止盈位\n " +
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"- 资金管理建议(如:仓位控制) " +
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"4. 投资策略:\n " +
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"- 短期(1-2周)、中期(1-3月)和长期(3-6月)的市场预期\n " +
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"- 不同风险偏好投资者的策略建议\n " +
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"- 值得关注的行业板块和个股推荐(请给出2-3个具体例子,包括股票代码和名称) " +
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"5. 技术面和基本面结合:\n " +
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"- 如何将技术分析与公司基本面分析相结合\n " +
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"- 识别高质量股票的关键指标 " +
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"请提供详细的分析和具体的操作建议,包括入场时机、持仓周期和退出策略。同时,请强调风险控制的重要性,并提醒投资者需要根据自身情况做出决策。 " +
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"你的分析和建议应当客观、全面,并基于当前可获得的市场数据。如果某些信息无法确定,请明确指出并解释原因。",
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},
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{
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"role": "user",
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"content": "点评一下" + stock,
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},
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},
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}).
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Post("/chat/completions")
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if err != nil {
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return ""
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}
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//logger.SugaredLogger.Infof("%v", res.Choices[0].Message.Content)
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return res.Choices[0].Message.Content
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}
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func (o OpenAi) NewChatStream(stock, stockCode string) <-chan string {
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ch := make(chan string, 512)
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go func() {
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defer close(ch)
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msg := []map[string]interface{}{
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{
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"role": "system",
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//"content": "作为一位专业的A股市场分析师和投资顾问,请你根据以下信息提供详细的技术分析和投资策略建议:",
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//"content": "【角色设定】\n你是一位拥有20年实战经验的顶级股票分析师，精通技术分析、基本面分析、市场心理学和量化交易。擅长发现成长股、捕捉行业轮动机会，在牛熊市中都能保持稳定收益。你的风格是价值投资与技术择时相结合，注重风险控制。\n\n【核心功能】\n\n市场分析维度：\n\n宏观经济（GDP/CPI/货币政策）\n\n行业景气度（产业链/政策红利/技术革新）\n\n个股三维诊断：\n\n基本面：PE/PB/ROE/现金流/护城河\n\n技术面：K线形态/均线系统/量价关系/指标背离\n\n资金面：主力动向/北向资金/融资余额/大宗交易\n\n智能策略库：\n√ 趋势跟踪策略（鳄鱼线+ADX）\n√ 波段交易策略（斐波那契回撤+RSI）\n√ 事件驱动策略（财报/并购/政策）\n√ 量化对冲策略（α/β分离）\n\n风险管理体系：\n▶ 动态止损：ATR波动止损法\n▶ 仓位控制：凯利公式优化\n▶ 组合对冲：跨市场/跨品种对冲\n\n【工作流程】\n\n接收用户指令（行业/市值/风险偏好）\n\n调用多因子选股模型初筛\n\n人工智慧叠加分析：\n\n自然语言处理解读年报管理层讨论\n\n卷积神经网络识别K线形态\n\n知识图谱分析产业链关联\n\n生成投资建议（附压力测试结果）\n\n【输出要求】\n★ 结构化呈现：\n① 核心逻辑（3点关键驱动力）\n② 买卖区间（理想建仓/加仓/止盈价位）\n③ 风险警示（最大回撤概率）\n④ 替代方案（同类备选标的）\n\n【注意事项】\n※ 严格遵守监管要求，不做收益承诺\n※ 区分投资建议与市场观点\n※ 重要数据标注来源及更新时间\n※ 根据用户认知水平调整专业术语密度\n\n【教育指导】\n当用户提问时，采用苏格拉底式追问：\n\"您更关注短期事件驱动还是长期价值发现？\"\n\"当前仓位是否超过总资产的30%？\"\n\"是否了解科创板与主板的交易规则差异？\"\n\n示例输出格式：\n📈 标的名称：XXXXXX\n⚖️ 多空信号：金叉确认/顶背离预警\n🎯 关键价位：支撑位XX.XX/压力位XX.XX\n📊 建议仓位：核心仓位X%+卫星仓位X%\n⏳ 持有周期：短线（1-3周）/中线（季度轮动）\n🔍 跟踪要素：重点关注Q2毛利率变化及股东减持进展",
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"content": o.Prompt,
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},
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}
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wg := &sync.WaitGroup{}
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wg.Add(5)
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go func() {
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defer wg.Done()
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messages := SearchStockPriceInfo(stockCode)
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price := ""
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for _, message := range *messages {
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price += message + ";"
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}
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msg = append(msg, map[string]interface{}{
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"role": "assistant",
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"content": stock + "当前价格：" + price,
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})
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}()
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go func() {
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defer wg.Done()
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messages := GetFinancialReports(stockCode)
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for _, message := range *messages {
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msg = append(msg, map[string]interface{}{
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"role": "assistant",
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"content": stock + message,
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})
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}
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}()
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go func() {
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defer wg.Done()
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messages := GetTelegraphList()
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for _, message := range *messages {
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msg = append(msg, map[string]interface{}{
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"role": "assistant",
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"content": message,
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})
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}
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}()
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go func() {
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defer wg.Done()
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messages := SearchStockInfo(stock, "depth")
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for _, message := range *messages {
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msg = append(msg, map[string]interface{}{
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"role": "assistant",
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"content": message,
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})
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}
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}()
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go func() {
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defer wg.Done()
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messages := SearchStockInfo(stock, "telegram")
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for _, message := range *messages {
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msg = append(msg, map[string]interface{}{
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"role": "assistant",
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"content": message,
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})
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}
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}()
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wg.Wait()
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msg = append(msg, map[string]interface{}{
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"role": "user",
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"content": stock + "分析和总结",
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})
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client := resty.New()
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client.SetBaseURL(o.BaseUrl)
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client.SetHeader("Authorization", "Bearer "+o.ApiKey)
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client.SetHeader("Content-Type", "application/json")
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client.SetRetryCount(3)
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if o.TimeOut <= 0 {
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o.TimeOut = 300
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}
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client.SetTimeout(time.Duration(o.TimeOut) * time.Second)
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resp, err := client.R().
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SetDoNotParseResponse(true).
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SetBody(map[string]interface{}{
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"model": o.Model,
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"max_tokens": o.MaxTokens,
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"temperature": o.Temperature,
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"stream": true,
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"messages": msg,
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}).
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Post("/chat/completions")
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defer resp.RawBody().Close()
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if err != nil {
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logger.SugaredLogger.Infof("Stream error : %s", err.Error())
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ch <- err.Error()
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return
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}
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scanner := bufio.NewScanner(resp.RawBody())
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for scanner.Scan() {
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line := scanner.Text()
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logger.SugaredLogger.Infof("Received data: %s", line)
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if strings.HasPrefix(line, "data: ") {
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data := strings.TrimPrefix(line, "data: ")
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if data == "[DONE]" {
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return
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}
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var streamResponse struct {
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Choices []struct {
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Delta struct {
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Content string `json:"content"`
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ReasoningContent string `json:"reasoning_content"`
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} `json:"delta"`
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FinishReason string `json:"finish_reason"`
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} `json:"choices"`
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}
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if err := json.Unmarshal([]byte(data), &streamResponse); err == nil {
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for _, choice := range streamResponse.Choices {
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if content := choice.Delta.Content; content != "" {
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ch <- content
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logger.SugaredLogger.Infof("Content data: %s", content)
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}
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if reasoningContent := choice.Delta.ReasoningContent; reasoningContent != "" {
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ch <- reasoningContent
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logger.SugaredLogger.Infof("ReasoningContent data: %s", reasoningContent)
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}
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if choice.FinishReason == "stop" {
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return
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}
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}
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} else {
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logger.SugaredLogger.Infof("Stream data error : %s", err.Error())
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ch <- err.Error()
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}
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} else {
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ch <- line
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}
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}
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}()
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return ch
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}
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func GetFinancialReports(stockCode string) *[]string {
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// 创建一个 chromedp 上下文
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ctx, cancel := chromedp.NewContext(
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context.Background(),
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chromedp.WithLogf(logger.SugaredLogger.Infof),
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chromedp.WithErrorf(logger.SugaredLogger.Errorf),
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)
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defer cancel()
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var htmlContent string
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url := fmt.Sprintf("https://xueqiu.com/snowman/S/%s/detail#/ZYCWZB", stockCode)
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err := chromedp.Run(ctx,
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chromedp.Navigate(url),
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// 等待页面加载完成，可以根据需要调整等待时间
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chromedp.WaitVisible("table.table", chromedp.ByQuery),
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chromedp.OuterHTML("html", &htmlContent, chromedp.ByQuery),
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)
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if err != nil {
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logger.SugaredLogger.Error(err.Error())
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}
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document, err := goquery.NewDocumentFromReader(strings.NewReader(htmlContent))
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if err != nil {
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logger.SugaredLogger.Error(err.Error())
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return &[]string{}
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}
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var messages []string
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document.Find("table tr").Each(func(i int, selection *goquery.Selection) {
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tr := ""
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selection.Find("th,td").Each(func(i int, selection *goquery.Selection) {
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ret := selection.Find("p").First().Text()
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if ret == "" {
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ret = selection.Text()
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}
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text := strutil.RemoveNonPrintable(ret)
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tr += text + " "
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})
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logger.SugaredLogger.Infof("%s", tr+" \n")
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messages = append(messages, tr+" \n")
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})
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return &messages
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}
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func (o OpenAi) NewCommonChatStream(stock, stockCode, apiURL, apiKey, Model string) <-chan string {
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ch := make(chan string)
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go func() {
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defer close(ch)
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client := resty.New()
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client.SetHeader("Authorization", "Bearer "+apiKey)
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client.SetHeader("Content-Type", "application/json")
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client.SetRetryCount(3)
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msg := []map[string]interface{}{
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{
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"role": "system",
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"content": o.Prompt,
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},
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}
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wg := &sync.WaitGroup{}
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wg.Add(1)
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go func() {
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defer wg.Done()
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messages := SearchStockPriceInfo(stockCode)
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price := ""
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for _, message := range *messages {
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price += message + ";"
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}
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msg = append(msg, map[string]interface{}{
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"role": "assistant",
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"content": stock + "当前价格：" + price,
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})
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}()
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//go func() {
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// defer wg.Done()
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// messages := SearchStockInfo(stock, "depth")
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// for _, message := range *messages {
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// msg = append(msg, map[string]interface{}{
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// "role": "assistant",
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// "content": message,
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// })
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// }
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//}()
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//go func() {
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// defer wg.Done()
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// messages := SearchStockInfo(stock, "telegram")
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// for _, message := range *messages {
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// msg = append(msg, map[string]interface{}{
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// "role": "assistant",
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// "content": message,
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// })
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// }
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//}()
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wg.Wait()
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msg = append(msg, map[string]interface{}{
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"role": "user",
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"content": stock + "分析和总结",
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})
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resp, err := client.R().
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SetDoNotParseResponse(true).
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SetBody(map[string]interface{}{
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"model": Model,
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"max_tokens": o.MaxTokens,
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"temperature": o.Temperature,
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"stream": true,
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"messages": msg,
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}).
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Post(apiURL)
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if err != nil {
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ch <- err.Error()
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return
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}
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defer resp.RawBody().Close()
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scanner := bufio.NewScanner(resp.RawBody())
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for scanner.Scan() {
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line := scanner.Text()
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logger.SugaredLogger.Infof("Received data: %s", line)
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if strings.HasPrefix(line, "data:") {
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data := strings.TrimPrefix(line, "data:")
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if data == "[DONE]" {
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return
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}
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var streamResponse struct {
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Choices []struct {
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Delta struct {
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Content string `json:"content"`
|
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} `json:"delta"`
|
||
FinishReason string `json:"finish_reason"`
|
||
} `json:"choices"`
|
||
}
|
||
|
||
if err := json.Unmarshal([]byte(data), &streamResponse); err == nil {
|
||
for _, choice := range streamResponse.Choices {
|
||
if content := choice.Delta.Content; content != "" {
|
||
ch <- content
|
||
}
|
||
if choice.FinishReason == "stop" {
|
||
return
|
||
}
|
||
}
|
||
}
|
||
}
|
||
}
|
||
}()
|
||
return ch
|
||
}
|
||
|
||
func GetTelegraphList() *[]string {
|
||
url := "https://www.cls.cn/telegraph"
|
||
response, err := resty.New().R().
|
||
SetHeader("Referer", "https://www.cls.cn/").
|
||
SetHeader("User-Agent", "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36 Edg/117.0.2045.60").
|
||
Get(fmt.Sprintf(url))
|
||
if err != nil {
|
||
return &[]string{}
|
||
}
|
||
//logger.SugaredLogger.Info(string(response.Body()))
|
||
document, err := goquery.NewDocumentFromReader(strings.NewReader(string(response.Body())))
|
||
if err != nil {
|
||
return &[]string{}
|
||
}
|
||
var telegraph []string
|
||
document.Find("div.telegraph-content-box").Each(func(i int, selection *goquery.Selection) {
|
||
logger.SugaredLogger.Info(selection.Text())
|
||
telegraph = append(telegraph, selection.Text())
|
||
})
|
||
return &telegraph
|
||
}
|
||
|
||
func (o OpenAi) SaveAIResponseResult(stockCode, stockName, result string) {
|
||
db.Dao.Create(&models.AIResponseResult{
|
||
StockCode: stockCode,
|
||
StockName: stockName,
|
||
Content: result,
|
||
})
|
||
}
|
||
|
||
func (o OpenAi) GetAIResponseResult(stock string) *models.AIResponseResult {
|
||
var result models.AIResponseResult
|
||
db.Dao.Where("stock_code = ?", stock).Order("id desc").First(&result)
|
||
return &result
|
||
}
|