weichen
f1302ed5b3
Why: Allow consumers to download an immutable module revision without nested source checkouts or local path replacements. Evidence: SELF package tests and the prior canonical-path rejection are recorded in the Dev dependency-workspace task card; remote consumption is replayed against the committed candidate. Impact: Change the module identity and its Go imports while preserving API behavior. Existing historical submodule revisions remain buildable. Refs: Versioned dependencies U1/U3; feature/dependency-workspace
63 lines
1.8 KiB
Go
63 lines
1.8 KiB
Go
// Package intentsem 慢通道实现（I2 增量三）：把 agent-intent 的
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// SemanticScorer / CommandGenerator 端口接到宿主已有的向量与轻量模型
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// 能力上。两个实现都是可插拔的——装配层默认不接线（设置开关关），
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// 此时识别行为与 I1 完全一致。
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package intentsem
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import (
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"context"
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"math"
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core "git-ssh.u1680832.nyat.app/weichen/Agent-System-Core.git"
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)
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// EmbeddingScorer 用语义向量实现 agentintent.SemanticScorer：
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// 对 input 与每个 example 取向量，返回最大余弦相似度。
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// 任何错误都原样上抛——库侧约定 scorer 出错时识别保持 Ambiguous，
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// 不会使 Recognize 失败（fail-open 到规则层结论）。
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type EmbeddingScorer struct {
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Provider core.EmbeddingProvider
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}
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// Score 返回 input 与 examples 的最高余弦相似度，取值 [0,1]。
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func (s EmbeddingScorer) Score(ctx context.Context, input string, examples []string) (float64, error) {
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if s.Provider == nil || len(examples) == 0 {
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return 0, nil
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}
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texts := make([]string, 0, len(examples)+1)
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texts = append(texts, input)
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texts = append(texts, examples...)
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vecs, err := s.Provider.Embed(ctx, texts)
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if err != nil {
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return 0, err
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}
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if len(vecs) != len(texts) || len(vecs[0]) == 0 {
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return 0, nil
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}
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best := 0.0
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for _, v := range vecs[1:] {
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if sim := cosine(vecs[0], v); sim > best {
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best = sim
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}
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}
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return best, nil
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}
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// cosine 计算两个等长向量的余弦相似度；任一零向量或不等长返回 0。
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func cosine(a, b []float32) float64 {
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if len(a) == 0 || len(a) != len(b) {
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return 0
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}
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var dot, na, nb float64
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for i := range a {
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fa, fb := float64(a[i]), float64(b[i])
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dot += fa * fb
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na += fa * fa
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nb += fb * fb
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}
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if na == 0 || nb == 0 {
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return 0
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}
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return dot / (math.Sqrt(na) * math.Sqrt(nb))
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}
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