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https://github.com/ArvinLovegood/go-stock.git
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feat(app):集成AI工具并优化股票数据获取
- 在 App 结构中添加 AiTools 字段，用于存储 AI 工具配置 - 新增 AddTools 函数，定义了两个 AI 工具：SearchStockByIndicators 和 GetStockKLine- 修改 NewApp 函数，初始化时加载 AI 工具配置- 更新相关函数，支持使用 AI 工具进行股票数据查询- 优化股票 K 线数据获取逻辑，增加对不同市场股票代码的支持
This commit is contained in:
ArvinLovegood
parent
888a97e4d3
commit
6d345ae91d
73
app.go
73
app.go
@ -36,6 +36,7 @@ type App struct {
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cache *freecache.Cache
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cron *cron.Cron
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cronEntrys map[string]cron.EntryID
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AiTools []data.Tool
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}
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// NewApp creates a new App application struct
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@ -44,13 +45,60 @@ func NewApp() *App {
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cache := freecache.NewCache(cacheSize)
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c := cron.New(cron.WithSeconds())
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c.Start()
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var tools []data.Tool
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tools = AddTools(tools)
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return &App{
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cache: cache,
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cron: c,
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cronEntrys: make(map[string]cron.EntryID),
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AiTools: tools,
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}
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}
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func AddTools(tools []data.Tool) []data.Tool {
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tools = append(tools, data.Tool{
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Type: "function",
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Function: data.ToolFunction{
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Name: "SearchStockByIndicators",
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Description: "根据自然语言筛选股票，返回自然语言选股条件要求的股票所有相关数据。单独输入股票名称可以获取当前股票最新的股价交易数据和基础财务指标信息",
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Parameters: data.FunctionParameters{
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Type: "object",
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Properties: map[string]any{
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"words": map[string]any{
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"type": "string",
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"description": "选股自然语言,并且条件使用;分隔，或者条件使用,分隔。例1：创新药;PE<30;净利润增长率>50%。 例2：上证指数(指数名称)。 例3：长电科技(股票名称)",
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},
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},
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Required: []string{"words"},
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},
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},
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})
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tools = append(tools, data.Tool{
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Type: "function",
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Function: data.ToolFunction{
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Name: "GetStockKLine",
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Description: "获取股票日K线数据",
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Parameters: data.FunctionParameters{
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Type: "object",
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Properties: map[string]any{
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"days": map[string]any{
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"type": "string",
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"description": "日K数据条数",
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},
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"stockCode": map[string]any{
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"type": "string",
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"description": "股票代码（A股：sh,sz开头;港股hk开头,美股：us开头）",
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},
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},
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Required: []string{"days", "stockCode"},
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},
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},
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})
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return tools
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}
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// startup is called at application startup
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func (a *App) startup(ctx context.Context) {
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defer PanicHandler()
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@ -311,7 +359,7 @@ func (a *App) AddCronTask(follow data.FollowedStock) func() {
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return func() {
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go runtime.EventsEmit(a.ctx, "warnMsg", "开始自动分析"+follow.Name+"_"+follow.StockCode)
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ai := data.NewDeepSeekOpenAi(a.ctx)
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msgs := ai.NewChatStream(follow.Name, follow.StockCode, "", nil)
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msgs := ai.NewChatStream(follow.Name, follow.StockCode, "", nil, a.AiTools)
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var res strings.Builder
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chatId := ""
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@ -748,7 +796,7 @@ func (a *App) SendDingDingMessageByType(message string, stockCode string, msgTyp
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}
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func (a *App) NewChatStream(stock, stockCode, question string, sysPromptId *int) {
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msgs := data.NewDeepSeekOpenAi(a.ctx).NewChatStream(stock, stockCode, question, sysPromptId)
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msgs := data.NewDeepSeekOpenAi(a.ctx).NewChatStream(stock, stockCode, question, sysPromptId, a.AiTools)
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for msg := range msgs {
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runtime.EventsEmit(a.ctx, "newChatStream", msg)
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}
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@ -1129,26 +1177,7 @@ func (a *App) GlobalStockIndexes() map[string]any {
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}
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func (a *App) SummaryStockNews(question string, sysPromptId *int) {
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var tools []data.Tool
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tools = append(tools, data.Tool{
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Type: "function",
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Function: data.ToolFunction{
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Name: "SearchStockByIndicators",
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Description: "根据自然语言筛选股票，返回自然语言选股条件要求的股票所有相关数据。单独输入股票名称可以获取当前股票最新的股价交易数据和基础财务指标信息",
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Parameters: data.FunctionParameters{
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Type: "object",
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Properties: map[string]any{
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"words": map[string]any{
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"type": "string",
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"description": "选股自然语言,并且条件使用;分隔，或者条件使用,分隔。例1：创新药;PE<30;净利润增长率>50%。 例2：上证指数(指数名称)。 例3：长电科技(股票名称)",
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},
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},
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Required: []string{"words"},
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},
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},
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})
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msgs := data.NewDeepSeekOpenAi(a.ctx).NewSummaryStockNewsStreamWithTools(question, sysPromptId, tools)
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msgs := data.NewDeepSeekOpenAi(a.ctx).NewSummaryStockNewsStreamWithTools(question, sysPromptId, a.AiTools)
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for msg := range msgs {
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runtime.EventsEmit(a.ctx, "summaryStockNews", msg)
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}
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@ -191,7 +191,7 @@ func (o OpenAi) NewSummaryStockNewsStreamWithTools(userQuestion string, sysPromp
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}()
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wg.Wait()
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news := NewMarketNewsApi().GetNewsList("", 100)
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news := NewMarketNewsApi().GetNewsList("财联社电报", 500)
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messageText := strings.Builder{}
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for _, telegraph := range *news {
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messageText.WriteString("## " + telegraph.Time + ":" + "\n")
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@ -310,7 +310,7 @@ func (o OpenAi) NewSummaryStockNewsStream(userQuestion string, sysPromptId *int)
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return ch
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}
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func (o OpenAi) NewChatStream(stock, stockCode, userQuestion string, sysPromptId *int) <-chan map[string]any {
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func (o OpenAi) NewChatStream(stock, stockCode, userQuestion string, sysPromptId *int, tools []Tool) <-chan map[string]any {
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ch := make(chan map[string]any, 512)
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defer func() {
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@ -647,7 +647,11 @@ func (o OpenAi) NewChatStream(stock, stockCode, userQuestion string, sysPromptId
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//reqJson, _ := json.Marshal(msg)
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//logger.SugaredLogger.Errorf("Stream request: \n%s\n", reqJson)
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AskAi(o, err, msg, ch, question)
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if tools != nil && len(tools) > 0 {
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AskAiWithTools(o, err, msg, ch, question, tools)
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} else {
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AskAi(o, err, msg, ch, question)
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}
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}()
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return ch
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}
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@ -859,17 +863,30 @@ func AskAiWithTools(o OpenAi, err error, messages []map[string]interface{}, ch c
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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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ch <- map[string]any{
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"code": 1,
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"question": question,
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"chatId": streamResponse.Id,
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"model": streamResponse.Model,
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"content": content,
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"time": time.Now().Format(time.DateTime),
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//logger.SugaredLogger.Infof("Content data: %s", content)
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if content == "###" {
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currentAIContent.WriteString("\r\n" + content)
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ch <- map[string]any{
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"code": 1,
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"question": question,
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"chatId": streamResponse.Id,
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"model": streamResponse.Model,
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"content": "\r\n" + content,
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"time": time.Now().Format(time.DateTime),
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}
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} else {
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currentAIContent.WriteString(content)
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ch <- map[string]any{
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"code": 1,
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"question": question,
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"chatId": streamResponse.Id,
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"model": streamResponse.Model,
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"content": content,
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"time": time.Now().Format(time.DateTime),
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}
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}
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//logger.SugaredLogger.Infof("Content data: %s", content)
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currentAIContent.WriteString(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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@ -913,16 +930,16 @@ func AskAiWithTools(o OpenAi, err error, messages []map[string]interface{}, ch c
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"question": question,
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"chatId": streamResponse.Id,
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"model": streamResponse.Model,
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"content": "- ```开始调用工具：SearchStockByIndicators，\n参数：" + words + "``` " + "\n",
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"content": "\r\n```\r\n开始调用工具：SearchStockByIndicators，\n参数：" + words + "\r\n```\r\n",
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"time": time.Now().Format(time.DateTime),
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}
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res := NewSearchStockApi(words).SearchStock(10)
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res := NewSearchStockApi(words).SearchStock(50)
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searchRes, _ := json.Marshal(res)
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content := gjson.Get(string(searchRes), "data.result").String()
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logger.SugaredLogger.Infof("SearchStockByIndicators:words:%s --> %s", words, content)
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//logger.SugaredLogger.Infof("SearchStockByIndicators:words:%s --> %s", words, content)
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//messages = append(messages, map[string]interface{}{
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// "role": "assistant",
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@ -935,6 +952,31 @@ func AskAiWithTools(o OpenAi, err error, messages []map[string]interface{}, ch c
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})
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}
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if funcName == "GetStockKLine" {
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stockCode := gjson.Get(funcArguments, "stockCode").String()
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days := gjson.Get(funcArguments, "days").String()
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ch <- map[string]any{
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"code": 1,
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"question": question,
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"chatId": streamResponse.Id,
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"model": streamResponse.Model,
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"content": "\r\n```\r\n开始调用工具：GetStockKLine，\n参数：" + stockCode + "," + days + "\r\n```\r\n",
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"time": time.Now().Format(time.DateTime),
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}
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toIntDay, err := convertor.ToInt(days)
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if err != nil {
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toIntDay = 90
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}
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res := NewStockDataApi().GetHK_KLineData(stockCode, "day", toIntDay)
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searchRes, _ := json.Marshal(res)
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messages = append(messages, map[string]interface{}{
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"role": "tool",
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"content": stockCode + convertor.ToString(toIntDay) + "日K线数据：\n" + string(searchRes) + "\n",
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"tool_call_id": currentCallId,
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})
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}
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AskAiWithTools(o, err, messages, ch, question, tools)
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}
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}
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