Initial commit of Descrybe v2 without local scratch artifacts.

Drop one-shot tmp/axe scripts and agent i18n scratch so the Gitea tree is deployable.

apps/api/internal/processing/pinecone.go

@@ -0,0 +1,133 @@
+package processing
+
+import (
+	"bytes"
+	"context"
+	"encoding/json"
+	"errors"
+	"io"
+	"net/http"
+	"strings"
+	"time"
+)
+
+// PineconeCategorizer implements VectorCategorizer via Pinecone query API.
+// When Embedder is set (admin AI role "vectorization" / env fallback), queries
+// send an explicit vector; otherwise Text is used (Pinecone integrated inference).
+// ASSUMPTION: when not configured, Enabled() is false and callers skip vector categorize.
+type PineconeCategorizer struct {
+	APIKey     string
+	Host       string
+	Namespace  string
+	HTTPClient *http.Client
+	Embedder   Embedder
+}
+
+func NewPineconeCategorizer(apiKey, host, namespace string) *PineconeCategorizer {
+	return &PineconeCategorizer{
+		APIKey:     strings.TrimSpace(apiKey),
+		Host:       strings.TrimRight(strings.TrimSpace(host), "/"),
+		Namespace:  namespace,
+		HTTPClient: &http.Client{Timeout: 20 * time.Second},
+	}
+}
+
+func (p *PineconeCategorizer) Enabled() bool {
+	return p != nil && p.APIKey != "" && p.Host != ""
+}
+
+type pineconeQueryRequest struct {
+	Namespace       string    `json:"namespace,omitempty"`
+	TopK            int       `json:"topK"`
+	IncludeMetadata bool      `json:"includeMetadata"`
+	Vector          []float32 `json:"vector,omitempty"`
+	Text            string    `json:"text,omitempty"`
+}
+
+type pineconeQueryResponse struct {
+	Matches []struct {
+		ID       string         `json:"id"`
+		Score    float64        `json:"score"`
+		Metadata map[string]any `json:"metadata"`
+	} `json:"matches"`
+}
+
+func (p *PineconeCategorizer) SuggestCategory(ctx context.Context, companyID, productText string, candidates []string) (string, error) {
+	if !p.Enabled() {
+		return "", errors.New("pinecone not configured")
+	}
+	productText = SanitizeText(productText)
+	if productText == "" {
+		return "", errors.New("empty product text")
+	}
+	_ = companyID
+	_ = candidates
+
+	reqBody := pineconeQueryRequest{
+		Namespace:       p.Namespace,
+		TopK:            1,
+		IncludeMetadata: true,
+	}
+	if p.Embedder != nil {
+		vecs, err := p.Embedder.Embed(ctx, []string{productText})
+		if err != nil {
+			return "", err
+		}
+		if len(vecs) == 0 || len(vecs[0]) == 0 {
+			return "", errors.New("empty embedding")
+		}
+		reqBody.Vector = vecs[0]
+	} else {
+		reqBody.Text = productText
+	}
+
+	body, err := json.Marshal(reqBody)
+	if err != nil {
+		return "", err
+	}
+	req, err := http.NewRequestWithContext(ctx, http.MethodPost, p.Host+"/query", bytes.NewReader(body))
+	if err != nil {
+		return "", err
+	}
+	req.Header.Set("Content-Type", "application/json")
+	req.Header.Set("Api-Key", p.APIKey)
+
+	res, err := p.HTTPClient.Do(req)
+	if err != nil {
+		return "", err
+	}
+	defer res.Body.Close()
+	raw, err := io.ReadAll(io.LimitReader(res.Body, 1<<20))
+	if err != nil {
+		return "", err
+	}
+	if res.StatusCode >= 400 {
+		return "", errors.New(TruncateError(errors.New("pinecone query failed")))
+	}
+	var parsed pineconeQueryResponse
+	if err := json.Unmarshal(raw, &parsed); err != nil {
+		return "", err
+	}
+	if len(parsed.Matches) == 0 {
+		return "", errors.New("no pinecone matches")
+	}
+	m := parsed.Matches[0].Metadata
+	if m != nil {
+		if name, ok := m["category"].(string); ok && strings.TrimSpace(name) != "" {
+			return SanitizeOutput(name), nil
+		}
+		if name, ok := m["name"].(string); ok && strings.TrimSpace(name) != "" {
+			return SanitizeOutput(name), nil
+		}
+	}
+	return SanitizeOutput(parsed.Matches[0].ID), nil
+}
+
+// NoopVectorCategorizer is the default when Pinecone is unset.
+type NoopVectorCategorizer struct{}
+
+func (NoopVectorCategorizer) Enabled() bool { return false }
+
+func (NoopVectorCategorizer) SuggestCategory(context.Context, string, string, []string) (string, error) {
+	return "", errors.New("vector categorizer disabled")
+}