wizardchen
16f2a46465
Remove FAQ bypass in agent rerank, apply composite model scores, and filter low-confidence results using configurable rerank_threshold.
78 lines
2.1 KiB
Go
78 lines
2.1 KiB
Go
package tools
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import (
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"testing"
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"github.com/Tencent/WeKnora/internal/config"
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"github.com/Tencent/WeKnora/internal/models/rerank"
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"github.com/Tencent/WeKnora/internal/types"
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)
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func TestFilterRerankRankResults_thresholdAndFallback(t *testing.T) {
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t.Parallel()
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rankResults := []rerank.RankResult{
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{Index: 0, RelevanceScore: 0.05},
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{Index: 1, RelevanceScore: 0.02},
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}
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filtered := filterRerankRankResults(rankResults, 0.3)
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if len(filtered) != 0 {
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t.Fatalf("expected empty filter, got %#v", filtered)
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}
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rankResults = []rerank.RankResult{
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{Index: 0, RelevanceScore: 0.05},
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{Index: 1, RelevanceScore: 0.20},
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}
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filtered = filterRerankRankResults(rankResults, 0.3)
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if len(filtered) != 1 || filtered[0].Index != 1 {
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t.Fatalf("expected fallback top score, got %#v", filtered)
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}
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rankResults = []rerank.RankResult{
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{Index: 0, RelevanceScore: 0.8},
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{Index: 1, RelevanceScore: 0.4},
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{Index: 2, RelevanceScore: 0.1},
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}
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filtered = filterRerankRankResults(rankResults, 0.3)
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if len(filtered) != 2 {
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t.Fatalf("expected 2 passing scores, got %#v", filtered)
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}
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}
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func TestApplyModelRerankScores_faqUsesCompositeScale(t *testing.T) {
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t.Parallel()
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tool := &KnowledgeSearchTool{
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config: &config.Config{
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Conversation: &config.ConversationConfig{RerankThreshold: 0.3},
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},
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}
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originals := []*searchResultWithMeta{
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{
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SearchResult: &types.SearchResult{ID: "faq-1", Content: "Q: WeKnora", Score: 0.011},
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KnowledgeBaseType: types.KnowledgeBaseTypeFAQ,
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},
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{
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SearchResult: &types.SearchResult{ID: "doc-1", Content: "swimming club", Score: 0.02},
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},
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}
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rankResults := []rerank.RankResult{
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{Index: 0, RelevanceScore: 0.05},
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{Index: 1, RelevanceScore: 0.9},
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}
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out := tool.applyModelRerankScores(originals, rankResults, 0.3)
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if len(out) != 1 || out[0].ID != "doc-1" {
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t.Fatalf("weak FAQ should be filtered out, got %#v", out)
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}
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if out[0].Score <= 0.011 {
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t.Fatalf("composite score should exceed raw retrieval score, got %.4f", out[0].Score)
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}
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}
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func TestRerankThreshold_default(t *testing.T) {
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t.Parallel()
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tool := &KnowledgeSearchTool{}
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if got := tool.rerankThreshold(); got != 0.3 {
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t.Fatalf("default threshold = %v, want 0.3", got)
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}
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}
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