chore(deps):指标选股问题

- 将 User-Agent 中的 Firefox 版本从 140.0 更新为 145.0
fix(backend): 指标选股问题
2025-10-27 18:16:25 +08:00 · 2025-10-27 18:15:02 +08:00 · 2025-09-29 18:10:55 +08:00 · 2025-09-29 17:34:31 +08:00 · 2025-09-27 19:12:51 +08:00 · 2025-09-27 18:55:28 +08:00
11 changed files with 273 additions and 13 deletions
--- a/README.md
+++ b/README.md
@@ -62,7 +62,7 @@
 | 功能说明            | 状态 | 备注                                                                                                       |
 |-----------------|----|----------------------------------------------------------------------------------------------------------|
 | 股票分析知识库         | 🚧 | 未来计划                                                                                                     |
-| Ai智能选股          | 🚧 | Ai智能选股功能开发中(下半年重点开发计划)                                                                                   |
+| Ai智能选股          | ✅ | Ai智能选股功能(市场行情-》AI总结/AI智能体功能)                                                                             |
 | ETF支持           | 🚧 | ETF数据支持 (目前可以查看净值和估值)                                                                                    |
 | 美股支持            | ✅  | 美股数据支持                                                                                                   |
 | 港股支持            | ✅  | 港股数据支持                                                                                                   |
--- a/app.go
+++ b/app.go
@@ -131,6 +131,50 @@ func AddTools(tools []data.Tool) []data.Tool {
 		},
 	})

+	//tools = append(tools, data.Tool{
+	//	Type: "function",
+	//	Function: data.ToolFunction{
+	//		Name:        "QueryBKDictInfo",
+	//		Description: "获取所有板块/行业名称或者代码(bkCode,bkName)",
+	//	},
+	//})
+
+	//tools = append(tools, data.Tool{
+	//	Type: "function",
+	//	Function: data.ToolFunction{
+	//		Name:        "GetIndustryResearchReport",
+	//		Description: "获取行业/板块研究报告,请先使用QueryBKDictInfo工具获取行业代码，然后输入行业代码调用",
+	//		Parameters: data.FunctionParameters{
+	//			Type: "object",
+	//			Properties: map[string]any{
+	//				"bkCode": map[string]any{
+	//					"type":        "string",
+	//					"description": "板块/行业代码",
+	//				},
+	//			},
+	//			Required: []string{"bkCode"},
+	//		},
+	//	},
+	//})
+
+	tools = append(tools, data.Tool{
+		Type: "function",
+		Function: data.ToolFunction{
+			Name:        "GetStockResearchReport",
+			Description: "获取股票的分析/研究报告",
+			Parameters: data.FunctionParameters{
+				Type: "object",
+				Properties: map[string]any{
+					"stockCode": map[string]any{
+						"type":        "string",
+						"description": "股票代码",
+					},
+				},
+				Required: []string{"stockCode"},
+			},
+		},
+	})
+
 	return tools
 }

--- a/backend/agent/agent.go
+++ b/backend/agent/agent.go
@@ -73,6 +73,7 @@ func GetStockAiAgent(ctx *context.Context, aiConfig data.AIConfig) *react.Agent
 			tools.GetFinancialReportTool(),
 			tools.GetQueryStockNewsTool(),
 			tools.GetIndustryResearchReportTool(),
+			tools.GetQueryBKDictTool(),
 		},
 	}
 	// 创建 agent
--- a/backend/agent/tools/bk_dict_tool.go
+++ b/backend/agent/tools/bk_dict_tool.go
@@ -0,0 +1,34 @@
+package tools
+
+import (
+	"context"
+	"encoding/json"
+	"go-stock/backend/data"
+
+	"github.com/cloudwego/eino/components/tool"
+	"github.com/cloudwego/eino/schema"
+	"github.com/coocood/freecache"
+)
+
+// @Author spark
+// @Date 2025/9/27 14:09
+// @Desc
+// -----------------------------------------------------------------------------------
+type ToolQueryBKDict struct{}
+
+func (t ToolQueryBKDict) Info(ctx context.Context) (*schema.ToolInfo, error) {
+	return &schema.ToolInfo{
+		Name: "QueryBKDictInfo",
+		Desc: "获取所有板块/行业名称或者代码(bkCode,bkName)",
+	}, nil
+}
+
+func (t ToolQueryBKDict) InvokableRun(ctx context.Context, argumentsInJSON string, opts ...tool.Option) (string, error) {
+	resp := data.NewMarketNewsApi().EMDictCode("016", freecache.NewCache(100))
+	bytes, err := json.Marshal(resp)
+	return string(bytes), err
+}
+
+func GetQueryBKDictTool() tool.InvokableTool {
+	return &ToolQueryBKDict{}
+}
--- a/backend/data/market_news_api.go
+++ b/backend/data/market_news_api.go
@@ -117,6 +117,27 @@ func (m MarketNewsApi) GetNewsList(source string, limit int) *[]*models.Telegrap
 	}
 	return news
 }
+func (m MarketNewsApi) GetNewsList2(source string, limit int) *[]*models.Telegraph {
+	news := &[]*models.Telegraph{}
+	if source != "" {
+		db.Dao.Model(news).Preload("TelegraphTags").Where("source=?", source).Order("id desc,is_red desc").Limit(limit).Find(news)
+	} else {
+		db.Dao.Model(news).Preload("TelegraphTags").Order("id desc,is_red desc").Limit(limit).Find(news)
+	}
+	for _, item := range *news {
+		tags := &[]models.Tags{}
+		db.Dao.Model(&models.Tags{}).Where("id in ?", lo.Map(item.TelegraphTags, func(item models.TelegraphTags, index int) uint {
+			return item.TagId
+		})).Find(&tags)
+		tagNames := lo.Map(*tags, func(item models.Tags, index int) string {
+			return item.Name
+		})
+		item.SubjectTags = tagNames
+		logger.SugaredLogger.Infof("tagNames %v ，SubjectTags：%s", tagNames, item.SubjectTags)
+	}
+	return news
+}
+
 func (m MarketNewsApi) GetTelegraphList(source string) *[]*models.Telegraph {
 	news := &[]*models.Telegraph{}
 	if source != "" {
--- a/backend/data/market_news_api_test.go
+++ b/backend/data/market_news_api_test.go
@@ -4,6 +4,7 @@ import (
 	"encoding/json"
 	"go-stock/backend/db"
 	"go-stock/backend/logger"
+	"go-stock/backend/models"
 	"go-stock/backend/util"
 	"strings"
 	"testing"
@@ -72,9 +73,12 @@ func TestLongTiger(t *testing.T) {

 func TestStockResearchReport(t *testing.T) {
 	db.Init("../../data/stock.db")
-	resp := NewMarketNewsApi().StockResearchReport("600584.sh", 7)
+	resp := NewMarketNewsApi().StockResearchReport("688082", 7)
 	for _, a := range resp {
 		logger.SugaredLogger.Debugf("value: %+v", a)
+		data := a.(map[string]any)
+		logger.SugaredLogger.Debugf("value: %s  infoCode:%s", data["title"], data["infoCode"])
+		NewMarketNewsApi().GetIndustryReportInfo(data["infoCode"].(string))
 	}
 }

@@ -108,7 +112,11 @@ func TestEMDictCode(t *testing.T) {
 	if err != nil {
 		return
 	}
+	dict := &[]models.BKDict{}
+	json.Unmarshal(bytes, dict)
 	logger.SugaredLogger.Debugf("value: %s", string(bytes))
+	md := util.MarkdownTableWithTitle("行业/板块代码", dict)
+	logger.SugaredLogger.Debugf(md)

 }

--- a/backend/data/openai_api.go
+++ b/backend/data/openai_api.go
@@ -324,7 +324,7 @@ func (o *OpenAi) NewSummaryStockNewsStreamWithTools(userQuestion string, sysProm
 		}()
 		wg.Wait()

-		news := NewMarketNewsApi().GetNewsList("财联社电报", random.RandInt(100, 500))
+		news := NewMarketNewsApi().GetNewsList2("财联社电报", random.RandInt(100, 500))
 		messageText := strings.Builder{}
 		for _, telegraph := range *news {
 			messageText.WriteString("## " + telegraph.Time + ":" + "\n")
@@ -473,7 +473,7 @@ func (o *OpenAi) NewSummaryStockNewsStream(userQuestion string, sysPromptId *int

 		wg.Wait()

-		news := NewMarketNewsApi().GetNewsList("", 100)
+		news := NewMarketNewsApi().GetNewsList2("财联社电报", random.RandInt(100, 500))
 		messageText := strings.Builder{}
 		for _, telegraph := range *news {
 			messageText.WriteString("## " + telegraph.Time + ":" + "\n")
@@ -1366,6 +1366,140 @@ func AskAiWithTools(o *OpenAi, err error, messages []map[string]interface{}, ch
 									"tool_call_id": currentCallId,
 								})
 							}
+							//
+							//if funcName == "QueryBKDictInfo" {
+							//	ch <- map[string]any{
+							//		"code":     1,
+							//		"question": question,
+							//		"chatId":   streamResponse.Id,
+							//		"model":    streamResponse.Model,
+							//		"content":  "\r\n```\r\n开始调用工具：QueryBKDictInfo，\n参数：" + funcArguments + "\r\n```\r\n",
+							//		"time":     time.Now().Format(time.DateTime),
+							//	}
+							//	res := NewMarketNewsApi().EMDictCode("016", freecache.NewCache(100))
+							//	bytes, err := json.Marshal(res)
+							//	if err != nil {
+							//		return
+							//	}
+							//	dict := &[]models.BKDict{}
+							//	json.Unmarshal(bytes, dict)
+							//	md := util.MarkdownTableWithTitle("行业/板块代码", dict)
+							//	logger.SugaredLogger.Infof("行业/板块代码=\n%s", md)
+							//	messages = append(messages, map[string]interface{}{
+							//		"role":    "assistant",
+							//		"content": currentAIContent.String(),
+							//		"tool_calls": []map[string]any{
+							//			{
+							//				"id":           currentCallId,
+							//				"tool_call_id": currentCallId,
+							//				"type":         "function",
+							//				"function": map[string]string{
+							//					"name":       funcName,
+							//					"arguments":  funcArguments,
+							//					"parameters": funcArguments,
+							//				},
+							//			},
+							//		},
+							//	})
+							//	messages = append(messages, map[string]interface{}{
+							//		"role":         "tool",
+							//		"content":      md,
+							//		"tool_call_id": currentCallId,
+							//	})
+							//}
+
+							//if funcName == "GetIndustryResearchReport" {
+							//	bkCode := gjson.Get(funcArguments, "bkCode").String()
+							//	ch <- map[string]any{
+							//		"code":     1,
+							//		"question": question,
+							//		"chatId":   streamResponse.Id,
+							//		"model":    streamResponse.Model,
+							//		"content":  "\r\n```\r\n开始调用工具：GetIndustryResearchReport，\n参数：" + bkCode + "\r\n```\r\n",
+							//		"time":     time.Now().Format(time.DateTime),
+							//	}
+							//	bkCode = strutil.ReplaceWithMap(bkCode, map[string]string{
+							//		"-":   "",
+							//		"_":   "",
+							//		"bk":  "",
+							//		"BK":  "",
+							//		"bk0": "",
+							//		"BK0": "",
+							//	})
+							//
+							//	logger.SugaredLogger.Debugf("code:%s", bkCode)
+							//	codeStr := convertor.ToString(bkCode)
+							//	res := NewMarketNewsApi().IndustryResearchReport(codeStr, 7)
+							//	md := strings.Builder{}
+							//	for _, a := range res {
+							//		d := a.(map[string]any)
+							//		md.WriteString(NewMarketNewsApi().GetIndustryReportInfo(d["infoCode"].(string)))
+							//	}
+							//	logger.SugaredLogger.Infof("bkCode:%s IndustryResearchReport:\n %s", bkCode, md.String())
+							//	messages = append(messages, map[string]interface{}{
+							//		"role":    "assistant",
+							//		"content": currentAIContent.String(),
+							//		"tool_calls": []map[string]any{
+							//			{
+							//				"id":           currentCallId,
+							//				"tool_call_id": currentCallId,
+							//				"type":         "function",
+							//				"function": map[string]string{
+							//					"name":       funcName,
+							//					"arguments":  funcArguments,
+							//					"parameters": funcArguments,
+							//				},
+							//			},
+							//		},
+							//	})
+							//	messages = append(messages, map[string]interface{}{
+							//		"role":         "tool",
+							//		"content":      md.String(),
+							//		"tool_call_id": currentCallId,
+							//	})
+							//}
+
+							if funcName == "GetStockResearchReport" {
+								stockCode := gjson.Get(funcArguments, "stockCode").String()
+								ch <- map[string]any{
+									"code":     1,
+									"question": question,
+									"chatId":   streamResponse.Id,
+									"model":    streamResponse.Model,
+									"content":  "\r\n```\r\n开始调用工具：GetStockResearchReport，\n参数：" + stockCode + "\r\n```\r\n",
+									"time":     time.Now().Format(time.DateTime),
+								}
+								res := NewMarketNewsApi().StockResearchReport(stockCode, 7)
+								md := strings.Builder{}
+								for _, a := range res {
+									logger.SugaredLogger.Debugf("value: %+v", a)
+									d := a.(map[string]any)
+									logger.SugaredLogger.Debugf("value: %s  infoCode:%s", d["title"], d["infoCode"])
+									md.WriteString(NewMarketNewsApi().GetIndustryReportInfo(d["infoCode"].(string)))
+								}
+								logger.SugaredLogger.Infof("stockCode:%s StockResearchReport:\n %s", stockCode, md.String())
+								messages = append(messages, map[string]interface{}{
+									"role":    "assistant",
+									"content": currentAIContent.String(),
+									"tool_calls": []map[string]any{
+										{
+											"id":           currentCallId,
+											"tool_call_id": currentCallId,
+											"type":         "function",
+											"function": map[string]string{
+												"name":       funcName,
+												"arguments":  funcArguments,
+												"parameters": funcArguments,
+											},
+										},
+									},
+								})
+								messages = append(messages, map[string]interface{}{
+									"role":         "tool",
+									"content":      md.String(),
+									"tool_call_id": currentCallId,
+								})
+							}

 						}
 						AskAiWithTools(o, err, messages, ch, question, tools)
--- a/backend/data/search_stock_api.go
+++ b/backend/data/search_stock_api.go
@@ -3,9 +3,10 @@ package data
 import (
 	"encoding/json"
 	"fmt"
-	"github.com/go-resty/resty/v2"
 	"go-stock/backend/logger"
 	"time"
+
+	"github.com/go-resty/resty/v2"
 )

 // @Author spark
@@ -25,25 +26,25 @@ func (s SearchStockApi) SearchStock(pageSize int) map[string]any {
 		SetHeader("Host", "np-tjxg-g.eastmoney.com").
 		SetHeader("Origin", "https://xuangu.eastmoney.com").
 		SetHeader("Referer", "https://xuangu.eastmoney.com/").
-		SetHeader("User-Agent", "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:140.0) Gecko/20100101 Firefox/140.0").
+		SetHeader("User-Agent", "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:145.0) Gecko/20100101 Firefox/145.0").
 		SetHeader("Content-Type", "application/json").
 		SetBody(fmt.Sprintf(`{
 				"keyWord": "%s",
 				"pageSize": %d,
 				"pageNo": 1,
-				"fingerprint": "e38b5faabf9378c8238e57219f0ebc9b",
+				"fingerprint": "02efa8944b1f90fbfe050e1e695a480d",
 				"gids": [],
 				"matchWord": "",
-				"timestamp": "1751113883290349",
+				"timestamp": "%d",
 				"shareToGuba": false,
-				"requestId": "8xTWgCDAjvQ5lmvz5mDA3Ydk2AE4yoiJ1751113883290",
+				"requestId": "RMd3Y76AJI98axPvdhdbKvbBDVwLlUK61761559950168",
 				"needCorrect": true,
 				"removedConditionIdList": [],
-				"xcId": "xc0af28549ab330013ed",
+				"xcId": "xc0d61279aad33008260",
 				"ownSelectAll": false,
 				"dxInfo": [],
 				"extraCondition": ""
-				}`, s.words, pageSize)).Post(url)
+				}`, s.words, pageSize, time.Now().Unix())).Post(url)
 	if err != nil {
 		logger.SugaredLogger.Errorf("SearchStock-err:%+v", err)
 		return map[string]any{}
--- a/backend/data/search_stock_api_test.go
+++ b/backend/data/search_stock_api_test.go
@@ -2,16 +2,18 @@ package data

 import (
 	"encoding/json"
-	"github.com/duke-git/lancet/v2/convertor"
 	"go-stock/backend/db"
 	"go-stock/backend/logger"
 	"testing"
+
+	"github.com/duke-git/lancet/v2/convertor"
 )

 func TestSearchStock(t *testing.T) {
 	db.Init("../../data/stock.db")

 	res := NewSearchStockApi("算力股;净利润连续3年增长").SearchStock(10)
+	logger.SugaredLogger.Infof("res:%+v", res)
 	data := res["data"].(map[string]any)
 	result := data["result"].(map[string]any)
 	dataList := result["dataList"].([]any)
--- a/backend/models/models.go
+++ b/backend/models/models.go
@@ -1,9 +1,10 @@
 package models

 import (
+	"time"
+
 	"gorm.io/gorm"
 	"gorm.io/plugin/soft_delete"
-	"time"
 )

 // @Author spark
@@ -687,3 +688,16 @@ type CailianpressWeb struct {
 		Author  string `json:"author" md:"资讯发布者"`
 	} `json:"list"`
 }
+
+type BKDict struct {
+	gorm.Model  `md:"-"`
+	BkCode      string `json:"bkCode" md:"行业/板块代码"`
+	BkName      string `json:"bkName" md:"行业/板块名称"`
+	FirstLetter string `json:"firstLetter" md:"first_letter"`
+	FubkCode    string `json:"fubkCode" md:"fubk_code"`
+	PublishCode string `json:"publishCode" md:"publish_code"`
+}
+
+func (b BKDict) TableName() string {
+	return "bk_dict"
+}
--- a/main.go
+++ b/main.go
@@ -228,6 +228,7 @@ func AutoMigrate() {
 	db.Dao.AutoMigrate(&models.TelegraphTags{})
 	db.Dao.AutoMigrate(&models.LongTigerRankData{})
 	db.Dao.AutoMigrate(&data.AIConfig{})
+	db.Dao.AutoMigrate(&models.BKDict{})

 	updateMultipleModel()
 }
Author	SHA1	Message	Date
ArvinLovegood	1d81fdba87	chore(deps):指标选股问题 - 将 User-Agent 中的 Firefox 版本从 140.0 更新为 145.0	2025-10-27 18:16:25 +08:00
ArvinLovegood	6aca0e15cc	fix(backend): 指标选股问题 - 修改fingerprint和requestId为新的固定值 - 将timestamp设置为动态生成的时间戳 - 更新xcId为新的标识符 - 在测试中增加返回结果的日志输出	2025-10-27 18:15:02 +08:00
ArvinLovegood	173ce6f243	fix(backend):修复新闻列表排序逻辑 - 将新闻列表按ID降序排列，确保最新新闻优先显示 - 保持is_red字段的降序排序，确保重要新闻优先显示 - 修复了查询条件中缺少的排序字段逗号问题	2025-09-29 18:10:55 +08:00
ArvinLovegood	e7875e73d3	feat(backend):新增并使用GetNewsList2方法以支持标签功能 - 在MarketNewsApi中添加GetNewsList2方法，支持根据source和limit获取新闻列表 - GetNewsList2方法中预加载TelegraphTags并关联标签名称 - 修改openai_api.go中调用GetNewsList的地方为GetNewsList2- 调整获取新闻列表的参数，使用固定source和随机limit值	2025-09-29 17:34:31 +08:00
ArvinLovegood	ca4727db80	fix(app):更新股票研究报告工具描述 - 修改了GetStockResearchReport函数的描述信息 - 简化了描述文本，去除冗余的"机构的"前缀 - 保持了原有功能和参数结构不变	2025-09-27 19:12:51 +08:00
ArvinLovegood	84ffe7c5fd	refactor(openai_api):移除行业板块相关工具调用逻辑 - 注释掉QueryBKDictInfo工具的调用实现 - 注释掉GetIndustryResearchReport工具的调用实现 - 移除对freecache包的依赖引用- 保留GetStockResearchReport工具的调用逻辑 - 简化工具调用处理流程	2025-09-27 18:55:28 +08:00
ArvinLovegood	da02d1bd1c	feat(stock):更新股票研究报接口参数并完善行业研究描述 - 修改行业研究工具函数描述，增加调用前需查询行业代码的提示 - 更新股票研究报接口测试用例中的股票代码参数值 - 完善行业研究报相关功能的使用说明和参数校验逻辑- 优化研究报数据获取流程，提升接口稳定性与准确性	2025-09-27 16:59:05 +08:00
ArvinLovegood	bae2bf9c5c	docs(readme): 更新AI智能选股功能描述 - 在功能说明中添加AI智能体功能的描述 - 保持其他功能状态和备注信息不变	2025-09-27 15:46:33 +08:00
ArvinLovegood	6568b5949a	docs(readme): 更新AI智能选股功能状态 - 将AI智能选股功能状态从开发中更新为已完成 - 修改功能描述为"市场行情-》AI总结" - 调整了功能备注信息的表述方式	2025-09-27 15:44:03 +08:00
ArvinLovegood	c4287f9b78	feat(ai):新增了机构/券商的研究报告AI工具函数 - 添加 QueryBKDictInfo 工具用于获取板块/行业字典信息 - 实现 GetIndustryResearchReport 工具用于获取行业研究报告 - 实现 GetStockResearchReport 工具用于获取股票研究报告 - 在数据库中新增 BKDict 模型并自动迁移 - 更新 MarketNewsApi 测试用例以支持新工具调用 - 在 OpenAI API 中集成新工具的调用逻辑与响应处理	2025-09-27 15:39:37 +08:00
ArvinLovegood	87441d8923	feat(ai):新增了机构/券商的研究报告AI工具函数 - 添加 QueryBKDictInfo 工具用于获取板块/行业字典信息 - 实现 GetIndustryResearchReport 工具用于获取行业研究报告 - 实现 GetStockResearchReport 工具用于获取股票研究报告 - 在数据库中新增 BKDict 模型并自动迁移 - 更新 MarketNewsApi 测试用例以支持新工具调用 - 在 OpenAI API 中集成新工具的调用逻辑与响应处理	2025-09-27 15:39:25 +08:00