Closes SPEC §3.4. The matrix indexer is now a learning meta-index per
feedback_meta_index_vision.md — every successful (query → answer)
pair recorded via /matrix/playbooks/record boosts that answer for
future similar queries.
This is the architectural piece that lifts vectord from "static
hybrid search" to the meta-index J originally framed in Phase 19 of
the Rust system.
What's new:
- internal/matrix/playbook.go — PlaybookEntry, PlaybookHit,
ApplyPlaybookBoost. Pure-function boost math:
distance' = distance * (1 - 0.5 * score)
Score 0 = no boost (factor 1.0); score 1 = halve distance
(factor 0.5). Capped at 0.5 deliberately so a single high-
confidence playbook can't dominate the base ranking forever
(runaway-feedback-loop guard).
- Retriever.Record(entry, corpus) — embeds query_text, ensures
playbook corpus exists (idempotent), upserts via deterministic
sha256-derived ID (last score wins on re-record of same triple).
- Retriever.Search extended with UsePlaybook + PlaybookCorpus +
PlaybookTopK + PlaybookMaxDistance. Reuses the query vector —
no extra embed call. Missing-corpus 404 = no-op (cold-start
state before any Record call), not an error.
- POST /v1/matrix/playbooks/record (matrixd) — caller submits
{query_text, answer_id, answer_corpus, score, tags?}; gets
{playbook_id} back.
Storage: a vectord index named "playbook_memory" (configurable per
request) with embed(query_text) as the vector and the
PlaybookEntry JSON as metadata. Just another corpus — observable
from /vectors/index, persistable through G1P, etc.
Match key for boost: (AnswerID, AnswerCorpus). Cross-corpus ID
collisions don't false-match — verified by
TestApplyPlaybookBoost_CorpusAttributionRespected.
End-to-end smoke (scripts/playbook_smoke.sh, all assertions PASS):
- Baseline search: widget-c at distance 0.6566 (rank 3)
- Record playbook: query → widget-c, score=1.0
- Re-search with use_playbook=true:
widget-c distance: 0.3283 (rank 2)
ratio: 0.5 EXACTLY (matches boost math precisely)
playbook_boosted: 1
- widget-c jumped from #3 to #2 — learning loop visible
Tests:
- 8 unit tests in internal/matrix/playbook_test.go covering
Validate, BoostFactor (5 cases), the no-boost identity, the
boost-moves-result-up scenario, highest-score wins on duplicate
matches, cross-corpus attribution, JSON round-trip, and
rejection of empty metadata
- scripts/playbook_smoke.sh integration test (3 assertions PASS)
15-smoke regression sweep all green (D1-D6, G1, G1P, G2,
storaged_cap, pathway, matrix, relevance, downgrade, playbook).
SPEC §3.4 NOW COMPLETE: 5 of 5 components shipped. The matrix
indexer's port is done as a substrate; remaining work is operational
(rating signal sources, telemetry, eventual structured filtering for
staffing data — none in §3.4).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
224 lines
7.1 KiB
Go
224 lines
7.1 KiB
Go
// matrixd is the matrix indexer service. Wraps internal/matrix's
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// Retriever with HTTP routes per docs/SPEC.md §3.4.
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//
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// Routes:
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// POST /matrix/search — multi-corpus retrieve+merge,
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// with optional playbook boost
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// GET /matrix/corpora — list known vectord indexes
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// POST /matrix/relevance — adjacency-pollution filter
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// POST /matrix/downgrade — strong-model downgrade gate
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// POST /matrix/playbooks/record — record a (query → answer)
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// success for the learning loop
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//
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// matrixd talks to embedd (for query-text embedding) and vectord
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// (for per-corpus search) via HTTP. Both URLs come from
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// [matrixd] config; gateway sets them to its own upstream URLs so
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// matrixd inherits the same provider topology.
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package main
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import (
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"encoding/json"
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"errors"
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"flag"
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"log/slog"
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"net/http"
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"os"
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"strings"
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"github.com/go-chi/chi/v5"
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"git.agentview.dev/profit/golangLAKEHOUSE/internal/matrix"
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"git.agentview.dev/profit/golangLAKEHOUSE/internal/shared"
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)
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const maxRequestBytes = 4 << 20 // 4 MiB cap on request bodies
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func main() {
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configPath := flag.String("config", "lakehouse.toml", "path to TOML config")
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flag.Parse()
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cfg, err := shared.LoadConfig(*configPath)
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if err != nil {
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slog.Error("config", "err", err)
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os.Exit(1)
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}
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if cfg.Matrixd.EmbeddURL == "" || cfg.Matrixd.VectordURL == "" {
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slog.Error("matrixd: embedd_url and vectord_url required in [matrixd]")
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os.Exit(1)
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}
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retriever := matrix.New(cfg.Matrixd.EmbeddURL, cfg.Matrixd.VectordURL)
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h := &handlers{r: retriever}
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if err := shared.Run("matrixd", cfg.Matrixd.Bind, h.register, cfg.Auth); err != nil {
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slog.Error("server", "err", err)
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os.Exit(1)
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}
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}
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type handlers struct {
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r *matrix.Retriever
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}
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func (h *handlers) register(r chi.Router) {
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r.Post("/matrix/search", h.handleSearch)
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r.Get("/matrix/corpora", h.handleCorpora)
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r.Post("/matrix/relevance", h.handleRelevance)
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r.Post("/matrix/downgrade", h.handleDowngrade)
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r.Post("/matrix/playbooks/record", h.handlePlaybookRecord)
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}
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func (h *handlers) handleSearch(w http.ResponseWriter, r *http.Request) {
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var req matrix.SearchRequest
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if !decodeJSON(w, r, &req) {
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return
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}
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resp, err := h.r.Search(r.Context(), req)
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if err != nil {
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writeMatrixError(w, err)
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return
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}
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writeJSON(w, http.StatusOK, resp)
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}
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// relevanceRequest is the POST /matrix/relevance body. Threshold
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// defaults to matrix.DefaultRelevanceThreshold when zero.
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type relevanceRequest struct {
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Focus matrix.FocusFile `json:"focus"`
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Chunks []matrix.CandidateChunk `json:"chunks"`
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Threshold float64 `json:"threshold,omitempty"`
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}
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func (h *handlers) handleRelevance(w http.ResponseWriter, r *http.Request) {
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var req relevanceRequest
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if !decodeJSON(w, r, &req) {
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return
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}
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if len(req.Chunks) == 0 {
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http.Error(w, "chunks must be non-empty", http.StatusBadRequest)
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return
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}
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threshold := req.Threshold
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if threshold == 0 {
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threshold = matrix.DefaultRelevanceThreshold
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}
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res := matrix.FilterChunks(req.Focus, req.Chunks, threshold)
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writeJSON(w, http.StatusOK, res)
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}
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// playbookRecordRequest is the POST /matrix/playbooks/record body.
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// Corpus is optional; defaults to matrix.DefaultPlaybookCorpus.
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type playbookRecordRequest struct {
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QueryText string `json:"query_text"`
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AnswerID string `json:"answer_id"`
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AnswerCorpus string `json:"answer_corpus"`
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Score float64 `json:"score"`
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Tags []string `json:"tags,omitempty"`
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Corpus string `json:"corpus,omitempty"`
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}
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func (h *handlers) handlePlaybookRecord(w http.ResponseWriter, r *http.Request) {
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var req playbookRecordRequest
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if !decodeJSON(w, r, &req) {
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return
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}
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entry := matrix.NewPlaybookEntry(req.QueryText, req.AnswerID, req.AnswerCorpus, req.Score, req.Tags)
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if err := entry.Validate(); err != nil {
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http.Error(w, err.Error(), http.StatusBadRequest)
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return
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}
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pbID, err := h.r.Record(r.Context(), entry, req.Corpus)
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if err != nil {
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slog.Warn("playbook record", "err", err)
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http.Error(w, err.Error(), http.StatusBadGateway)
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return
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}
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writeJSON(w, http.StatusOK, map[string]any{
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"playbook_id": pbID,
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"query_text": entry.QueryText,
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"answer_id": entry.AnswerID,
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"answer_corpus": entry.AnswerCorpus,
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"score": entry.Score,
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})
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}
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// downgradeRequest is the POST /matrix/downgrade body. Mirrors
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// matrix.DowngradeInput; ForceFullOverride is read from the
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// LH_FORCE_FULL_ENRICHMENT env var when omitted from the body.
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type downgradeRequest struct {
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Mode string `json:"mode"`
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Model string `json:"model"`
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ForcedMode bool `json:"forced_mode,omitempty"`
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ForceFullOverride *bool `json:"force_full_override,omitempty"`
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}
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func (h *handlers) handleDowngrade(w http.ResponseWriter, r *http.Request) {
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var req downgradeRequest
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if !decodeJSON(w, r, &req) {
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return
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}
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if req.Mode == "" || req.Model == "" {
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http.Error(w, "mode and model are required", http.StatusBadRequest)
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return
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}
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in := matrix.NewDowngradeInputFromEnv(req.Mode, req.Model, req.ForcedMode)
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if req.ForceFullOverride != nil {
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// Explicit body override beats env, useful for tooling that
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// wants to ask "what would the gate do under these conditions"
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// without env pollution.
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in.ForceFullOverride = *req.ForceFullOverride
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}
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writeJSON(w, http.StatusOK, matrix.MaybeDowngrade(in))
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}
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func (h *handlers) handleCorpora(w http.ResponseWriter, r *http.Request) {
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names, err := h.r.Corpora(r.Context())
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if err != nil {
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slog.Error("matrix corpora", "err", err)
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http.Error(w, "vectord unavailable", http.StatusBadGateway)
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return
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}
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writeJSON(w, http.StatusOK, map[string]any{"corpora": names, "count": len(names)})
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}
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func decodeJSON(w http.ResponseWriter, r *http.Request, v any) bool {
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defer r.Body.Close()
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r.Body = http.MaxBytesReader(w, r.Body, maxRequestBytes)
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if err := json.NewDecoder(r.Body).Decode(v); err != nil {
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var maxErr *http.MaxBytesError
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if errors.As(err, &maxErr) || strings.Contains(err.Error(), "http: request body too large") {
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http.Error(w, "body too large", http.StatusRequestEntityTooLarge)
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return false
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}
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http.Error(w, "decode body: "+err.Error(), http.StatusBadRequest)
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return false
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}
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return true
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}
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func writeJSON(w http.ResponseWriter, code int, v any) {
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w.Header().Set("Content-Type", "application/json")
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w.WriteHeader(code)
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if err := json.NewEncoder(w).Encode(v); err != nil {
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slog.Warn("matrix write json", "err", err)
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}
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}
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// writeMatrixError maps internal/matrix sentinels to HTTP statuses.
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// Corpus / embed failures bubble up as 502 (the upstream service is
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// what's wrong); validation errors are 400.
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func writeMatrixError(w http.ResponseWriter, err error) {
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switch {
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case errors.Is(err, matrix.ErrEmptyCorpora),
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errors.Is(err, matrix.ErrEmptyQuery):
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http.Error(w, err.Error(), http.StatusBadRequest)
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case errors.Is(err, matrix.ErrCorpus),
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errors.Is(err, matrix.ErrEmbed):
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slog.Warn("matrix upstream", "err", err)
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http.Error(w, err.Error(), http.StatusBadGateway)
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default:
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slog.Error("matrix", "err", err)
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http.Error(w, "internal", http.StatusInternalServerError)
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}
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}
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