Janady13/missionmatch / internal/modules/ai/memory.go

Source identity

Field	Recorded value
Source type	GitHub source
Original record	Janady13/missionmatch / internal/modules/ai/memory.go
Date	Not specified in source
Repository	Janady13/missionmatch
Revision	720d47fae476b0d38477ae4401697d372b1ea2bc
Branch	feature/opportunity-to-outcome
Path or archive member	internal/modules/ai/memory.go
Original SHA-256	f20d9abc85fdfdee2cbc3d216fb4cf1ce259f6cbf9ddd1e2b9793b9aa015b82c
Git blob SHA	82f51c27cea26c5d44acbcc86fb5bbce1dc07ffb
Reading-copy SHA-256	f20d9abc85fdfdee2cbc3d216fb4cf1ce259f6cbf9ddd1e2b9793b9aa015b82c

Original source ↗

Every recorded occurrence

These 23 records contain identical original source bytes. Their paths and revisions remain part of the archive.

Original record	Branch or archive	Revision / identifier	Original location
Janady13/missionmatch / internal/modules/ai/memory.go	feature/opportunity-to-outcome	720d47fae476b0d38477ae4401697d372b1ea2bc	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	per-tenant-routing	9bde0f9a74b89d01980fa658e5253acda7528d0c	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	collision-deconfliction	4ee5a09972608ed89f8377c6665542d5f450f0a6	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	ws6-retrieval	6c56e29231ec05735927fa265c97d517499dfeaf	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	m5-price-to-win	41000ad30fff4129fdaf5ec84e15ba14c27d4890	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	ws1-ontology-sync	b596f449a32a1016fbd403c36505cc00a1ac9ee6	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	master	1e9249840a4302ec82e123b9c9cb6f75badea3e4	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	ws8-teaching-loop	c823f0fb6bb2aba0f39001eb6de96f4000d9321f	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	mag-substrate	b82c7100a492dec67dfd1eda6b3f53def859be35	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	ws3-clearance	4b8e7ce594c068621867f9c9deed0ec64ae6c553	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	phase2-eval-fairness	d361af254701975fe239927656ababb56374655e	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	time-to-fill-survival	b66e1e505863d4f17741a4b9ede73509e45bd6c6	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	graphrag-foundation	b0ddeb9f633fd138d09309d1a17b7d13bc3a67f7	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	deploy-and-ops	bdacd9d0b4d5998d25fc74bf4007f4c3ec538c7a	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	ws9-bench-ingestion	f585a9ef32fa554663ce1fba9a414a54b6e49cf0	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	ws2-alias-relationship	e4dada4601c6eb101830f9d223a9655dfa120616	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	presentation-readiness	eb574acaa29d71ce4d0f852572e87c275c79fdb7	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	vendor-intelligence	fe9796a19c261951d3f2565206c0c1b5ac294465	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	ws7-federal-signal	6a9f6ce9cfb13345ffb47770d4960e7c2d9c17c2	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	ai-brain-live	aac32fc49c878cc5bca099459307611562d0bac1	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	phase2-connectors	e038d4c687aec16f8bd9bc4d907eea14d91f8704	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	feature/aioe-upgrade	2178e7298d0e5d9af83afa12402fd587f0ba6ed8	Open original
Janady13/missionmatch / internal/modules/ai/memory.go	capture-readiness	bae6af7cb2997e819174a9e9cfff5e16067a1975	Open original

Recovered source transcript

Download complete source text ↓126 lines · 4.2 KB

package ai

import (
	"context"
	"errors"
	"strconv"

	"github.com/google/uuid"
	"github.com/jackc/pgx/v5"

	"github.com/missionworkforce/missionmatch/internal/platform/inference"
	"github.com/missionworkforce/missionmatch/internal/platform/tenant"
)

// Memory is the per tenant episodic and semantic memory, stored in the tenant's own database (ai_memory)
// and therefore physically isolated from every other tenant. Episodic memory records what happened (a
// craft note about a turn); semantic memory holds a recallable fact with an embedding. No demographic
// data may enter memory: every write is eeo guarded. Memory about a candidate carries the candidate id,
// so the right to erasure wipes it (ForgetCandidate), the same way anonymize wipes the resume vector.
type Memory struct {
	db     *tenant.DB
	client *inference.Client
}

// NewMemory builds the per tenant memory over the tenant database and the inference client (for semantic
// recall embeddings).
func NewMemory(db *tenant.DB, client *inference.Client) *Memory {
	return &Memory{db: db, client: client}
}

// Store writes one memory. candidateID may be nil for a non candidate craft note. content is eeo guarded.
// A semantic memory is embedded so it can be recalled by similarity.
func (m *Memory) Store(ctx context.Context, candidateID *uuid.UUID, kind, content string) error {
	if m.db == nil {
		return errors.New("ai: no database")
	}
	if kind != "episodic" && kind != "semantic" {
		return errors.New("ai: memory kind must be episodic or semantic")
	}
	if err := ForbidEEO(content); err != nil {
		return err
	}
	var vecLit any
	if kind == "semantic" && m.client != nil {
		emb, err := m.client.Embed(ctx, []string{content})
		if err != nil {
			return err
		}
		vecLit = vectorLiteral(emb.Embeddings[0])
	}
	return m.db.RunInTenantTx(ctx, func(ctx context.Context, tx pgx.Tx) error {
		_, err := tx.Exec(ctx,
			"INSERT INTO ai_memory (organization_id, candidate_id, kind, content, embedding) "+
				"VALUES (NULLIF(current_setting('app.current_org_id', true),'')::uuid, $1, $2, $3, $4::vector)",
			candidateID, kind, content, vecLit)
		return err
	})
}

// ForgetCandidate is the standalone erasure hook: it deletes every memory about a candidate in its OWN
// tenant transaction, for an external caller, and it is exercised by the memory erasure integration test.
// The transactional erasure paths (sourcing.Delete and the governance retention sweep) inline the same
// DELETE on their EXISTING transaction instead, so the memory wipe commits atomically with the rest of the
// anonymize. Idempotent.
func (m *Memory) ForgetCandidate(ctx context.Context, candidateID uuid.UUID) error {
	if m.db == nil {
		return errors.New("ai: no database")
	}
	return m.db.RunInTenantTx(ctx, func(ctx context.Context, tx pgx.Tx) error {
		_, err := tx.Exec(ctx, "DELETE FROM ai_memory WHERE candidate_id = $1", candidateID)
		return err
	})
}

// Recall returns the semantically closest memories to a query (RLS scoped, eeo guarded). It is the
// retrieval side of memory augmented generation.
func (m *Memory) Recall(ctx context.Context, query string, limit int) ([]string, error) {
	if m.db == nil || m.client == nil {
		return nil, errors.New("ai: memory recall needs a database and a client")
	}
	if err := ForbidEEO(query); err != nil {
		return nil, err
	}
	if limit <= 0 || limit > 50 {
		limit = 5
	}
	emb, err := m.client.Embed(ctx, []string{query})
	if err != nil {
		return nil, err
	}
	lit := vectorLiteral(emb.Embeddings[0])
	var out []string
	err = m.db.RunInTenantTx(ctx, func(ctx context.Context, tx pgx.Tx) error {
		rows, err := tx.Query(ctx,
			"SELECT content FROM ai_memory WHERE embedding IS NOT NULL ORDER BY embedding <=> $1::vector LIMIT $2",
			lit, limit)
		if err != nil {
			return err
		}
		defer rows.Close()
		for rows.Next() {
			var c string
			if err := rows.Scan(&c); err != nil {
				return err
			}
			out = append(out, c)
		}
		return rows.Err()
	})
	return out, err
}

// vectorLiteral formats a 384 dim vector as a pgvector text literal for the $::vector cast.
func vectorLiteral(v []float32) string {
	b := make([]byte, 0, len(v)*8+2)
	b = append(b, '[')
	for i, x := range v {
		if i > 0 {
			b = append(b, ',')
		}
		b = strconv.AppendFloat(b, float64(x), 'f', -1, 32)
	}
	b = append(b, ']')
	return string(b)
}