Janady13/missionmatch / internal/platform/embeddings/megamind.go

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Field	Recorded value
Source type	GitHub source
Original record	Janady13/missionmatch / internal/platform/embeddings/megamind.go
Date	Not specified in source
Repository	Janady13/missionmatch
Revision	1e9249840a4302ec82e123b9c9cb6f75badea3e4
Branch	master
Path or archive member	internal/platform/embeddings/megamind.go
Original SHA-256	f442e925017eae348b833f7601c16431e5cb56d6f843c0ec5b968246374989b7
Git blob SHA	08d2c284356c6556b3864b9233f41dc096628fab
Reading-copy SHA-256	f442e925017eae348b833f7601c16431e5cb56d6f843c0ec5b968246374989b7

Original source ↗

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These 47 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/platform/embeddings/megamind.go	master	1e9249840a4302ec82e123b9c9cb6f75badea3e4	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	feature/aioe-upgrade	2178e7298d0e5d9af83afa12402fd587f0ba6ed8	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	m5-price-to-win	41000ad30fff4129fdaf5ec84e15ba14c27d4890	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	w3-ai-staffing-recommendations	43d56387270ef4da4cabd794d97ca6a49909bc7d	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ws3-clearance	4b8e7ce594c068621867f9c9deed0ec64ae6c553	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	collision-deconfliction	4ee5a09972608ed89f8377c6665542d5f450f0a6	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ai-intelligence-layer	5d5ddff70393a197c5f54a45280bb5dd42b24755	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ws7-federal-signal	6a9f6ce9cfb13345ffb47770d4960e7c2d9c17c2	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ws6-retrieval	6c56e29231ec05735927fa265c97d517499dfeaf	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	per-tenant-routing	9bde0f9a74b89d01980fa658e5253acda7528d0c	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ai-brain-live	aac32fc49c878cc5bca099459307611562d0bac1	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	graphrag-foundation	b0ddeb9f633fd138d09309d1a17b7d13bc3a67f7	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ws1-ontology-sync	b596f449a32a1016fbd403c36505cc00a1ac9ee6	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	time-to-fill-survival	b66e1e505863d4f17741a4b9ede73509e45bd6c6	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	mag-substrate	b82c7100a492dec67dfd1eda6b3f53def859be35	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	capture-readiness	bae6af7cb2997e819174a9e9cfff5e16067a1975	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	deploy-and-ops	bdacd9d0b4d5998d25fc74bf4007f4c3ec538c7a	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ws8-teaching-loop	c823f0fb6bb2aba0f39001eb6de96f4000d9321f	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	phase2-eval-fairness	d361af254701975fe239927656ababb56374655e	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	phase2-connectors	e038d4c687aec16f8bd9bc4d907eea14d91f8704	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ws2-alias-relationship	e4dada4601c6eb101830f9d223a9655dfa120616	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	presentation-readiness	eb574acaa29d71ce4d0f852572e87c275c79fdb7	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ws9-bench-ingestion	f585a9ef32fa554663ce1fba9a414a54b6e49cf0	Open original
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Janady13/missionmatch / internal/platform/embeddings/megamind.go	per-tenant-routing	9bde0f9a74b89d01980fa658e5253acda7528d0c	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	collision-deconfliction	4ee5a09972608ed89f8377c6665542d5f450f0a6	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ws6-retrieval	6c56e29231ec05735927fa265c97d517499dfeaf	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	m5-price-to-win	41000ad30fff4129fdaf5ec84e15ba14c27d4890	Open original
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Janady13/missionmatch / internal/platform/embeddings/megamind.go	master	1e9249840a4302ec82e123b9c9cb6f75badea3e4	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ws8-teaching-loop	c823f0fb6bb2aba0f39001eb6de96f4000d9321f	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	w3-ai-staffing-recommendations	43d56387270ef4da4cabd794d97ca6a49909bc7d	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	mag-substrate	b82c7100a492dec67dfd1eda6b3f53def859be35	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ws3-clearance	4b8e7ce594c068621867f9c9deed0ec64ae6c553	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	phase2-eval-fairness	d361af254701975fe239927656ababb56374655e	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	time-to-fill-survival	b66e1e505863d4f17741a4b9ede73509e45bd6c6	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ai-intelligence-layer	5d5ddff70393a197c5f54a45280bb5dd42b24755	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	graphrag-foundation	b0ddeb9f633fd138d09309d1a17b7d13bc3a67f7	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	deploy-and-ops	bdacd9d0b4d5998d25fc74bf4007f4c3ec538c7a	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ws9-bench-ingestion	f585a9ef32fa554663ce1fba9a414a54b6e49cf0	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ws2-alias-relationship	e4dada4601c6eb101830f9d223a9655dfa120616	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	presentation-readiness	eb574acaa29d71ce4d0f852572e87c275c79fdb7	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ws7-federal-signal	6a9f6ce9cfb13345ffb47770d4960e7c2d9c17c2	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	ai-brain-live	aac32fc49c878cc5bca099459307611562d0bac1	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	phase2-connectors	e038d4c687aec16f8bd9bc4d907eea14d91f8704	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	feature/aioe-upgrade	2178e7298d0e5d9af83afa12402fd587f0ba6ed8	Open original
Janady13/missionmatch / internal/platform/embeddings/megamind.go	capture-readiness	bae6af7cb2997e819174a9e9cfff5e16067a1975	Open original

Recovered source transcript

Download complete source text ↓61 lines · 1.8 KB

package embeddings

import (
	"context"
	"errors"

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

// megamindEmbedder is the Embedder backed by the stateless MEGAMIND inference plane. It is the
// production path for cleared CUI data: the embedding model runs out of process on the Apple Silicon
// cluster (Metal), and this adapter reaches it through the typed inference client (timeouts, retries,
// circuit breaker). It L2 normalizes the returned vectors so cosine distance over the pgvector column is
// meaningful, matching the contract every other provider here follows.
type megamindEmbedder struct {
	client *inference.Client
	dim    int
}

// newMegamind builds the MEGAMIND backed Embedder from the embeddings config.
func newMegamind(cfg config.Embeddings) (Embedder, error) {
	if cfg.MegamindURL == "" {
		return nil, errors.New("embeddings: MM_MEGAMIND_URL required for the megamind provider")
	}
	model := cfg.Model
	if model == "" {
		model = "all-minilm"
	}
	c, err := inference.New(inference.Config{
		BaseURL:    cfg.MegamindURL,
		EmbedModel: model,
		Dimension:  cfg.Dimension,
	})
	if err != nil {
		return nil, err
	}
	return &megamindEmbedder{client: c, dim: cfg.Dimension}, nil
}

func (m *megamindEmbedder) Dimension() int { return m.dim }

func (m *megamindEmbedder) Embed(ctx context.Context, text string) ([]float32, error) {
	out, err := m.EmbedBatch(ctx, []string{text})
	if err != nil {
		return nil, err
	}
	return out[0], nil
}

func (m *megamindEmbedder) EmbedBatch(ctx context.Context, texts []string) ([][]float32, error) {
	res, err := m.client.Embed(ctx, texts)
	if err != nil {
		return nil, err
	}
	for i := range res.Embeddings {
		normalize(res.Embeddings[i])
	}
	return res.Embeddings, nil
}