84 lines
3.1 KiB
Go
84 lines
3.1 KiB
Go
package rule
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import (
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"context"
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"encoding/json"
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"fmt"
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"os"
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"strings"
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"git.apinb.com/bsm-sdk/core/utils"
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"git.apinb.com/quant/gostock/internal/config"
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"github.com/go-deepseek/deepseek"
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"github.com/go-deepseek/deepseek/request"
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)
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var (
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MarkdataPath = "./markdata/"
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)
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func (r *RuleFactory) RunAi(code string) {
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mdPath := MarkdataPath + code + ".md"
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if !utils.PathExists(mdPath) {
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r.Model.AiScrore = -1
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r.Model.AddDesc(fmt.Sprintf("%s markdown 文件未找友", mdPath))
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return
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}
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content, err := os.ReadFile(mdPath)
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if err != nil {
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r.Model.AiScrore = -1
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r.Model.AddDesc(fmt.Sprintf("%s markdown 读取错误,%v", mdPath, err))
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return
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}
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client, _ := deepseek.NewClient(config.Spec.DeepSeekApiKey)
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//prompt := "你是一名资深量化投研分析师,分析" + code + "这个股票，该股票的详细数据在https://markdata.apinb.com/" + code + ".md 读取这个markdown格式的内容，根据内容中的行情，财报，技术指标等数据(倒序，最新在最前面），给出基本面总结，技术面总结，舆论总结等更多方面的总结，并输出买入评分（0-10）整数，输出JSON，字段：summary(500字内中文总结)、score(0-10数字)、action(买入/谨慎/观望)、risk(一句风险提示)。"
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prompt := "你是一名资深量化投研分析师,分析" + code + "这个股票，根据内容中的行情，财报，技术指标等数据，给出基本面总结，技术面总结，舆论总结等更多方面的总结，并输出买入评分（0-10）整数，输出JSON，字段：summary(中文总结)、summary_2025(2025年财报总结)、summary_base(基本面分析总结)、summary_tech(技术面分析总结)、score(0-10数字)、support_level(支撑位价格)、resis_level(阻力位价格)、action(买入/谨慎/观望)、risk(一句风险提示)。\r\n"
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prompt += "内容如下：\r\n"
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prompt += string(content)
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chatReq := &request.ChatCompletionsRequest{
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Model: deepseek.DEEPSEEK_CHAT_MODEL,
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Stream: false,
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Messages: []*request.Message{
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{
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Role: "system",
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Content: prompt, // set your input message
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},
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},
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}
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chatResp, err := client.CallChatCompletionsChat(context.Background(), chatReq)
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if err != nil {
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r.Model.AiScrore = -1
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r.Model.AddDesc(fmt.Sprintf("处理失败: %v", err))
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return
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}
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// 输出JSON格式的结果
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jsonBodys := strings.ReplaceAll(chatResp.Choices[0].Message.Content, "```json", "")
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jsonBodys = strings.ReplaceAll(jsonBodys, "```", "")
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var result map[string]any
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err = json.Unmarshal([]byte(jsonBodys), &result)
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if err != nil {
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r.Model.AiScrore = -1
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r.Model.AddDesc(fmt.Sprintf("Unmarshal: %v", err))
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return
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}
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r.Model.AiSummary = result["summary"].(string)
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r.Model.AiSummary2025 = result["summary_2025"].(string)
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r.Model.AiSummaryBase = result["summary_base"].(string)
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r.Model.AiSummaryTech = result["summary_tech"].(string)
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r.Model.AiScrore = int(result["score"].(float64))
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r.Model.AiSupportLevel = result["support_level"].(float64)
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r.Model.AiResisLevel = result["resis_level"].(float64)
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r.Model.AiAction = result["action"].(string)
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r.Model.AiRisk = result["risk"].(string)
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return
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}
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