t
18c9354095
- 注入数据库、运行时配置、统一响应、文件存储和平台 AI 能力，补充业务读写工具与客户快捷操作契约。 - 移除模块内重复的组织、客户、工单、标签、技能、旧工作流、MCP 和迁移实现，将身份权限与业务主体交由宿主管理。 - 使用 libSQL 重构向量存储，并完善图片消息、访客身份、排队调度、企业微信和支持聊天页面。 - 统一 HTTP、DTO 与 WebSocket 的 snake_case 协议，补齐模块初始化、业务动作和公共载荷等回归测试。
301 lines
8.5 KiB
Go
301 lines
8.5 KiB
Go
package rag
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import (
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"encoding/json"
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"fmt"
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"time"
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"code.tczkiot.com/wlw/ai-agent/internal/models"
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"code.tczkiot.com/wlw/ai-agent/internal/pkg/dto"
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"code.tczkiot.com/wlw/ai-agent/internal/pkg/dto/response"
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"github.com/google/uuid"
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"github.com/mlogclub/simple/sqls"
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)
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var RetrieveLog = &retrieveLog{}
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type retrieveLog struct {
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}
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type CreateRetrieveLogRequest struct {
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KnowledgeBaseID int64
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Channel string
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Scene string
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SessionID string
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ConversationID int64
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Question string
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RewriteQuestion string
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Answer string
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AnswerStatus int
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ChunkProvider string
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ChunkTargetTokens int
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ChunkMaxTokens int
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ChunkOverlapTokens int
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RerankEnabled bool
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RerankLimit int
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Hits []response.KnowledgeSearchResult
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UsedHits []response.KnowledgeSearchResult
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Citations []response.KnowledgeCitation
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LatencyMs int64
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RetrieveMs int64
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GenerateMs int64
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PromptTokens int
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CompletionTokens int
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ModelName string
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}
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type retrieveTraceData struct {
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Retrieve retrieveTraceRetrieve `json:"retrieve"`
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ChunkConfig retrieveTraceChunkConfig `json:"chunk_config"`
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Context retrieveTraceContext `json:"context"`
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Citations []retrieveTraceCitation `json:"citations"`
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}
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type retrieveTraceRetrieve struct {
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Provider string `json:"provider"`
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RerankEnabled bool `json:"rerank_enabled"`
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RerankLimit int `json:"rerank_limit"`
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RawHitCount int `json:"raw_hit_count"`
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ContextHitCount int `json:"context_hit_count"`
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CitationCount int `json:"citation_count"`
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}
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type retrieveTraceChunkConfig struct {
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Provider string `json:"provider"`
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TargetTokens int `json:"target_tokens"`
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MaxTokens int `json:"max_tokens"`
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OverlapTokens int `json:"overlap_tokens"`
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}
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type retrieveTraceContext struct {
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KnowledgeBaseIDs []int64 `json:"knowledge_base_ids"`
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DocumentIDs []int64 `json:"document_ids"`
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SectionPaths []string `json:"section_paths"`
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UsedChunkKeys []string `json:"used_chunk_keys"`
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}
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type retrieveTraceCitation struct {
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DocumentID int64 `json:"document_id"`
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ChunkNo int `json:"chunk_no"`
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SectionPath string `json:"section_path"`
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}
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func (s *retrieveLog) FindHitsByRetrieveLogID(retrieveLogID int64) []models.KnowledgeRetrieveHit {
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if retrieveLogID <= 0 {
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return nil
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}
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var list []models.KnowledgeRetrieveHit
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sqls.DB().Where("retrieve_log_id = ?", retrieveLogID).Order("rank_no asc, id asc").Find(&list)
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return list
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}
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func (s *retrieveLog) CreateRetrieveLog(req *CreateRetrieveLogRequest, _ *dto.AuthPrincipal) (*models.KnowledgeRetrieveLog, error) {
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if req == nil {
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return nil, fmt.Errorf("retrieve log request is nil")
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}
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now := time.Now()
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topScore := 0.0
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if len(req.Hits) > 0 {
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topScore = req.Hits[0].Score
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}
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traceData := buildRetrieveTraceData(req)
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log := &models.KnowledgeRetrieveLog{
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KnowledgeBaseID: req.KnowledgeBaseID,
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Channel: req.Channel,
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Scene: req.Scene,
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SessionID: req.SessionID,
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ConversationID: req.ConversationID,
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RequestID: uuid.New().String(),
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Question: req.Question,
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RewriteQuestion: req.RewriteQuestion,
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Answer: req.Answer,
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AnswerStatus: req.AnswerStatus,
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HitCount: len(req.Hits),
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TopScore: topScore,
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ChunkProvider: req.ChunkProvider,
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ChunkTargetTokens: req.ChunkTargetTokens,
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ChunkMaxTokens: req.ChunkMaxTokens,
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ChunkOverlapTokens: req.ChunkOverlapTokens,
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RerankEnabled: req.RerankEnabled,
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RerankLimit: req.RerankLimit,
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CitationCount: len(req.Citations),
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UsedChunkCount: len(req.UsedHits),
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LatencyMs: req.LatencyMs,
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RetrieveMs: req.RetrieveMs,
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GenerateMs: req.GenerateMs,
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PromptTokens: req.PromptTokens,
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CompletionTokens: req.CompletionTokens,
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ModelName: req.ModelName,
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TraceData: traceData,
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CreatedAt: now,
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}
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usedHitKeys := make(map[string]struct{}, len(req.UsedHits))
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for _, item := range req.UsedHits {
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usedHitKeys[buildKnowledgeSearchResultKey(item)] = struct{}{}
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}
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citationKeys := make(map[string]struct{}, len(req.Citations))
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for _, item := range req.Citations {
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citationKeys[buildKnowledgeCitationKey(item)] = struct{}{}
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}
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if err := sqls.WithTransaction(func(ctx *sqls.TxContext) error {
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if err := ctx.Tx.Create(log).Error; err != nil {
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return err
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}
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for i, hit := range req.Hits {
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hitKey := buildKnowledgeSearchResultKey(hit)
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hitRecord := &models.KnowledgeRetrieveHit{
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RetrieveLogID: log.ID,
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KnowledgeBaseID: hit.KnowledgeBaseID,
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ChunkID: hit.ChunkID,
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DocumentID: hit.DocumentID,
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DocumentTitle: hit.DocumentTitle,
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FaqID: hit.FaqID,
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FaqQuestion: hit.FaqQuestion,
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ChunkNo: hit.ChunkNo,
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Title: hit.Title,
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SectionPath: hit.SectionPath,
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ChunkType: "",
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Provider: req.ChunkProvider,
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RankNo: i + 1,
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Score: hit.Score,
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RerankScore: hit.RerankScore,
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UsedInAnswer: hasHitKey(usedHitKeys, hitKey),
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IsCitation: hasHitKey(citationKeys, hitKey),
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Snippet: hit.Content,
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CreatedAt: now,
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}
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if err := ctx.Tx.Create(hitRecord).Error; err != nil {
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return err
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}
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}
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return nil
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}); err != nil {
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return nil, err
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}
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return log, nil
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}
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func buildRetrieveTraceData(req *CreateRetrieveLogRequest) string {
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trace := retrieveTraceData{
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Retrieve: retrieveTraceRetrieve{
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Provider: req.ChunkProvider,
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RerankEnabled: req.RerankEnabled,
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RerankLimit: req.RerankLimit,
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RawHitCount: len(req.Hits),
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ContextHitCount: len(req.UsedHits),
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CitationCount: len(req.Citations),
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},
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ChunkConfig: retrieveTraceChunkConfig{
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Provider: req.ChunkProvider,
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TargetTokens: req.ChunkTargetTokens,
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MaxTokens: req.ChunkMaxTokens,
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OverlapTokens: req.ChunkOverlapTokens,
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},
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Context: retrieveTraceContext{
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KnowledgeBaseIDs: distinctKnowledgeBaseIDs(req.UsedHits),
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DocumentIDs: distinctDocumentIDs(req.UsedHits),
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SectionPaths: distinctSectionPaths(req.UsedHits),
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UsedChunkKeys: buildUsedChunkKeys(req.UsedHits),
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},
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Citations: buildTraceCitations(req.Citations),
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}
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data, err := json.Marshal(trace)
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if err != nil {
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return ""
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}
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return string(data)
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}
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func buildTraceCitations(citations []response.KnowledgeCitation) []retrieveTraceCitation {
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items := make([]retrieveTraceCitation, 0, len(citations))
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for _, item := range citations {
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items = append(items, retrieveTraceCitation{
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DocumentID: item.DocumentID,
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ChunkNo: item.ChunkNo,
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SectionPath: item.SectionPath,
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})
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}
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return items
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}
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func buildUsedChunkKeys(hits []response.KnowledgeSearchResult) []string {
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keys := make([]string, 0, len(hits))
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for _, item := range hits {
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keys = append(keys, buildKnowledgeSearchResultKey(item))
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}
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return keys
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}
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func distinctKnowledgeBaseIDs(hits []response.KnowledgeSearchResult) []int64 {
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ids := make([]int64, 0)
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seen := make(map[int64]struct{})
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for _, item := range hits {
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if item.KnowledgeBaseID <= 0 {
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continue
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}
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if _, ok := seen[item.KnowledgeBaseID]; ok {
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continue
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}
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seen[item.KnowledgeBaseID] = struct{}{}
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ids = append(ids, item.KnowledgeBaseID)
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}
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return ids
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}
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func distinctDocumentIDs(hits []response.KnowledgeSearchResult) []int64 {
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seen := make(map[int64]struct{})
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items := make([]int64, 0)
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for _, item := range hits {
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if item.DocumentID <= 0 {
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continue
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}
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if _, ok := seen[item.DocumentID]; ok {
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continue
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}
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seen[item.DocumentID] = struct{}{}
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items = append(items, item.DocumentID)
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}
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return items
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}
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func distinctSectionPaths(hits []response.KnowledgeSearchResult) []string {
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seen := make(map[string]struct{})
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items := make([]string, 0)
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for _, item := range hits {
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sectionPath := item.SectionPath
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if sectionPath == "" {
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continue
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}
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if _, ok := seen[sectionPath]; ok {
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continue
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}
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seen[sectionPath] = struct{}{}
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items = append(items, sectionPath)
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}
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return items
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}
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func buildKnowledgeSearchResultKey(item response.KnowledgeSearchResult) string {
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if item.FaqID > 0 {
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return fmt.Sprintf("faq:%d|%d", item.FaqID, item.ChunkNo)
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}
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return fmt.Sprintf("%d|%s|%d", item.DocumentID, item.SectionPath, item.ChunkNo)
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}
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func buildKnowledgeCitationKey(item response.KnowledgeCitation) string {
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if item.FaqID > 0 {
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return fmt.Sprintf("faq:%d|%d", item.FaqID, item.ChunkNo)
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}
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return fmt.Sprintf("%d|%s|%d", item.DocumentID, item.SectionPath, item.ChunkNo)
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}
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func hasHitKey(items map[string]struct{}, key string) bool {
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_, ok := items[key]
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return ok
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}
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