77 lines
3.2 KiB
Go
77 lines
3.2 KiB
Go
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package retrieval
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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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"data-terminal-cloud/internal/developmentembedding"
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"github.com/jackc/pgx/v5"
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)
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type Memory struct {
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MemoryID string `json:"memory_id"`
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MemoryVersionID string `json:"memory_version_id"`
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VersionNo int64 `json:"version_no"`
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Content string `json:"-"`
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SourceRefs json.RawMessage `json:"source_refs"`
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Sensitivity string `json:"sensitivity"`
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Relevance float64 `json:"relevance"`
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}
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// SelectMemoryForContext fixes the tenant and subject boundary in the SQL
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// itself. Callers cannot supply a free-form filter. The first production
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// baseline admits only normal-sensitivity memories into a voice context.
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func SelectMemoryForContext(ctx context.Context, tx pgx.Tx, tenantID, subjectID, query string, limit int) ([]Memory, error) {
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queryVector := developmentembedding.Literal(developmentembedding.Vector(query))
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return SelectMemoryForContextVector(ctx, tx, tenantID, subjectID, queryVector, limit)
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}
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// SelectMemoryForContextVector uses a vector generated before the caller's
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// transaction. This keeps production embedding network calls out of the
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// conversation creation transaction while retaining the SQL tenant, subject,
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// consent and lifecycle boundaries below.
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func SelectMemoryForContextVector(ctx context.Context, tx pgx.Tx, tenantID, subjectID, queryVector string, limit int) ([]Memory, error) {
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if limit < 1 || limit > 10 {
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return nil, fmt.Errorf("memory retrieval limit must be between 1 and 10")
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}
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if queryVector == "" {
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return nil, fmt.Errorf("memory retrieval vector is required")
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}
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rows, err := tx.Query(ctx, `
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SELECT cm.public_id::text,mv.public_id::text,mv.version_no,mv.content,mv.source_refs,
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cm.sensitivity,1-(mi.embedding <=> $3::vector) AS relevance
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FROM memory_index_entry mi
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JOIN curated_memory cm ON cm.id=mi.memory_id AND cm.tenant_id=mi.tenant_id AND cm.subject_id=mi.subject_id
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JOIN memory_version mv ON mv.id=mi.memory_version_id AND mv.memory_id=cm.id
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WHERE mi.tenant_id=$1::uuid AND mi.subject_id=$2::uuid
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AND mi.index_type='pgvector' AND mi.status='ACTIVE' AND mi.embedding IS NOT NULL
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AND cm.status='ACTIVE' AND cm.current_version_id=mv.id
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AND cm.sensitivity='normal'
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AND (cm.valid_from IS NULL OR cm.valid_from<=now())
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AND (cm.valid_to IS NULL OR cm.valid_to>now())
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AND EXISTS(SELECT 1 FROM consent_record cr
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WHERE cr.tenant_id=cm.tenant_id AND cr.subject_id=cm.subject_id
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AND cr.consent_type='personalized_memory' AND cr.withdrawn_at IS NULL
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AND (cr.expires_at IS NULL OR cr.expires_at>now()))
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ORDER BY mi.embedding <=> $3::vector,mv.confirmed_at DESC,mv.id
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LIMIT $4`, tenantID, subjectID, queryVector, limit)
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if err != nil {
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return nil, fmt.Errorf("query eligible memory: %w", err)
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}
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defer rows.Close()
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items := make([]Memory, 0, limit)
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for rows.Next() {
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var item Memory
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if err := rows.Scan(&item.MemoryID, &item.MemoryVersionID, &item.VersionNo, &item.Content, &item.SourceRefs, &item.Sensitivity, &item.Relevance); err != nil {
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return nil, fmt.Errorf("scan eligible memory: %w", err)
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}
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items = append(items, item)
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}
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if err := rows.Err(); err != nil {
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return nil, fmt.Errorf("iterate eligible memory: %w", err)
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}
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return items, nil
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}
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