AskaEth
cd83eec39e
- rag.Embedder: LLM API 文本向量化 (OpenAI-compatible) - rag.KnowledgeStore: 文档分块 + 重叠窗口 + 余弦相似度搜索 - rag.Retriever: 高级知识检索 + 格式化摘要 - KnowledgeProvider: 子会话提供者，整合入编排管线 - knowledge_search / knowledge_ingest 工具 - EnrichmentData 管线全线支持 KnowledgeInfo Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
62 lines
1.6 KiB
Go
62 lines
1.6 KiB
Go
package rag
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import (
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"context"
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"fmt"
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"strings"
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)
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// Retriever provides a high-level knowledge retrieval interface.
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type Retriever struct {
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store *KnowledgeStore
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}
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// NewRetriever creates a new knowledge retriever.
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func NewRetriever(store *KnowledgeStore) *Retriever {
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return &Retriever{store: store}
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}
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// Retrieve searches the knowledge base and returns formatted results.
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func (r *Retriever) Retrieve(ctx context.Context, query string, topK int) (*RetrievalResult, error) {
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results, err := r.store.Search(ctx, query, topK)
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if err != nil {
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return nil, fmt.Errorf("knowledge search: %w", err)
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}
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ret := &RetrievalResult{
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Query: query,
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Results: results,
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Summary: r.buildSummary(results),
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}
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return ret, nil
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}
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// RetrievalResult holds knowledge retrieval output.
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type RetrievalResult struct {
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Query string `json:"query"`
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Results []SearchResult `json:"results"`
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Summary string `json:"summary"`
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}
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func (r *Retriever) buildSummary(results []SearchResult) string {
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if len(results) == 0 {
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return "知识库中未找到相关信息。"
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}
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var sb strings.Builder
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sb.WriteString(fmt.Sprintf("从知识库中找到 %d 条相关信息:\n\n", len(results)))
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for i, result := range results {
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sb.WriteString(fmt.Sprintf("--- 来源: %s (段落 %d, 相关度 %.0f%%) ---\n",
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result.Chunk.DocTitle, result.Chunk.Index+1, result.Score*100))
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sb.WriteString(result.Chunk.Content)
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if i < len(results)-1 {
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sb.WriteString("\n\n")
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}
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}
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return sb.String()
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}
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// Stats returns knowledge base statistics.
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func (r *Retriever) Stats() map[string]interface{} {
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return r.store.Stats()
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}
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