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hyperguild/ingestion/internal/mcp/server.go
Mathias 57462b52ff
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feat(brain): hybrid BM25 + pgvector retrieval (opt-in)
Wires nomic-embed-text (iguana ollama) + pgvector on the shared
postgres18 into brain_query / brain_answer via Reciprocal Rank Fusion.
Pure BM25 stays the default; setting BRAIN_PG_DSN and BRAIN_EMBED_URL
together opts in. Setting one without the other is misconfiguration →
exit 1.

New packages:

- internal/embed
  Client.Embed(ctx, text) → []float32 via POST {URL}/api/embed.
  Defaults to nomic-embed-text:latest (768 dim). nil-on-empty-URL so
  callers gate on a single nil check.

- internal/vectorstore
  PGStore wraps a pgxpool against postgres18. Init creates
  brain_embeddings(path PK, vector(768), updated_at) + HNSW cosine
  index idempotently. Upsert / Delete / Search / KnownPaths.
  Sync(brainDir, store, embedder) diffs brain/wiki/ against the store
  and upserts new files / deletes removed ones; StartSync runs it on
  a ticker (default 300s). Integration tests gated by BRAIN_PG_TEST_DSN.

- scripts/brain-embeddings-init.sql
  One-time DBA setup: brain DB, brain_app role, vector extension,
  GRANTs. Idempotent.

Search layer:

- search.QueryOptions gains Vector + Embedder fields.
- QueryContext is the cancellable variant; Query stays for callers.
- When both are set, BM25 (top-N) and pgvector (top-4N) candidates
  merge via Reciprocal Rank Fusion (k=60, Cormack et al. 2009 — no
  tuning knob, robust to scale differences between rankers).
- Vector-only hits are hydrated from disk so callers see uniform
  Result records (path, title, excerpt, wing, hall, score).
- Wing/hall filters still apply to vector candidates via path-prefix.
- On embedder/vector errors the search falls back to BM25 — embedding
  outage degrades quality but doesn't take the brain offline.

MCP wiring:

- mcp.Server.WithHybridRetrieval(v, e) opt-in setter, same shape as
  WithReranker.
- brainQuery and brainAnswer pass the wired vector/embedder through
  to search.QueryContext.

REST:

- POST /backfill-embeddings drives Sync synchronously. Returns
  {added, deleted, errors[]}. 503 when feature is unconfigured.

cmd/server/main.go:

- BRAIN_PG_DSN + BRAIN_EMBED_URL together enable hybrid; one alone
  → exit 1.
- vectorAdapter bridges *PGStore (returns []Hit) to
  search.VectorSearcher (which takes []VectorHit) without either
  package importing the other.
- BRAIN_EMBED_SYNC_INTERVAL (default 300s) controls the background
  Sync ticker.

Backend pivot from Qdrant to pgvector recorded in DECISIONS.md
2026-05-18 (supersedes 2026-04-08): postgres18 already runs in
databases/ ns, Qdrant was never deployed, one engine beats two.

Dependency: github.com/jackc/pgx/v5 — modern, native pgvector via
parametric vector literals.

Tests:
- embed.Client: empty-URL nil, request shape, dimension, upstream
  error propagation, empty-text rejection.
- vectorstore.PGStore: dimension validation (unit); upsert/search/
  KnownPaths (integration, BRAIN_PG_TEST_DSN-gated).
- vectorstore.Sync: adds new files, skips known, deletes
  disappeared, skips _index.md, no-op when nil, collects embedder
  errors.
- search.Query: hybrid promotes vector-only hits via RRF; falls
  back to BM25 on embedder error.

Closes hyperguild#8.
2026-05-18 23:11:25 +02:00

181 lines
5.3 KiB
Go

// Package mcp implements an MCP HTTP handler for the ingestion service.
// Exposed tools: brain_query, brain_write, brain_index, brain_tunnel,
// brain_ingest, brain_ingest_raw, brain_answer, brain_classify, session_log.
package mcp
import (
"context"
"encoding/json"
"fmt"
"net/http"
"github.com/mathiasbq/hyperguild/ingestion/internal/pipeline"
"github.com/mathiasbq/hyperguild/ingestion/internal/reranker"
"github.com/mathiasbq/hyperguild/ingestion/internal/search"
)
type request struct {
JSONRPC string `json:"jsonrpc"`
ID any `json:"id"`
Method string `json:"method"`
Params json.RawMessage `json:"params"`
}
type response struct {
JSONRPC string `json:"jsonrpc"`
ID any `json:"id,omitempty"`
Result any `json:"result,omitempty"`
Error *rpcError `json:"error,omitempty"`
}
type rpcError struct {
Code int `json:"code"`
Message string `json:"message"`
}
// Server handles MCP JSON-RPC over HTTP for the ingestion service.
type Server struct {
brainDir string
pipeline pipeline.Config
llm pipeline.CompleteFunc
answerLLM pipeline.CompleteFunc // nil = brain_answer and brain_classify unavailable
reranker *reranker.Client // nil = no rerank, BM25 top-10 → LLM
vector search.VectorSearcher // nil = BM25-only retrieval
embedder search.Embedder // nil = BM25-only retrieval
}
// NewServer constructs a Server bound to brainDir. pipelineCfg supplies the
// LLM-backed pipeline; llm may be nil for non-LLM tools only.
// answerLLM drives brain_answer and brain_classify; nil disables those tools.
func NewServer(brainDir string, pipelineCfg *pipeline.Config, llm pipeline.CompleteFunc, answerLLM pipeline.CompleteFunc) *Server {
cfg := pipeline.Config{}
if pipelineCfg != nil {
cfg = *pipelineCfg
}
return &Server{brainDir: brainDir, pipeline: cfg, llm: llm, answerLLM: answerLLM}
}
// WithReranker installs an opt-in cross-encoder reranker. When set,
// brain_answer retrieves a wider BM25 candidate set and prunes it to
// the relevant ones before LLM synthesis. Returns the server for
// fluent chaining.
func (s *Server) WithReranker(r *reranker.Client) *Server {
s.reranker = r
return s
}
// WithHybridRetrieval wires the embedding store and embedder so
// brain_query and brain_answer run BM25 + pgvector merged via RRF
// instead of BM25 alone. Either nil disables hybrid mode.
func (s *Server) WithHybridRetrieval(v search.VectorSearcher, e search.Embedder) *Server {
s.vector = v
s.embedder = e
return s
}
func (s *Server) ServeHTTP(w http.ResponseWriter, r *http.Request) {
// MCP streamable HTTP: GET establishes the SSE stream for server-to-client events.
if r.Method == http.MethodGet {
w.Header().Set("Content-Type", "text/event-stream")
w.Header().Set("Cache-Control", "no-cache")
w.Header().Set("Connection", "keep-alive")
w.Header().Set("X-Accel-Buffering", "no")
w.WriteHeader(http.StatusOK)
if f, ok := w.(http.Flusher); ok {
f.Flush()
}
<-r.Context().Done()
return
}
var req request
if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
writeError(w, nil, -32700, "parse error")
return
}
// JSON-RPC 2.0 notifications (no id) must not receive a response.
if req.ID == nil {
return
}
var result any
var rpcErr *rpcError
switch req.Method {
case "initialize":
result = map[string]any{
"protocolVersion": "2024-11-05",
"capabilities": map[string]any{"tools": map[string]any{}},
"serverInfo": map[string]any{"name": "ingestion-brain", "version": "0.1.0"},
}
case "tools/list":
result = map[string]any{"tools": s.tools()}
case "tools/call":
var p struct {
Name string `json:"name"`
Arguments json.RawMessage `json:"arguments"`
}
if err := json.Unmarshal(req.Params, &p); err != nil {
rpcErr = &rpcError{Code: -32602, Message: "invalid params"}
break
}
out, err := s.handleCall(r.Context(), p.Name, p.Arguments)
if err != nil {
rpcErr = &rpcError{Code: -32000, Message: err.Error()}
break
}
result = map[string]any{
"content": []map[string]any{{"type": "text", "text": string(out)}},
}
default:
rpcErr = &rpcError{Code: -32601, Message: "method not found: " + req.Method}
}
w.Header().Set("Content-Type", "application/json")
_ = json.NewEncoder(w).Encode(response{
JSONRPC: "2.0",
ID: req.ID,
Result: result,
Error: rpcErr,
})
}
func writeError(w http.ResponseWriter, id any, code int, msg string) {
w.Header().Set("Content-Type", "application/json")
_ = json.NewEncoder(w).Encode(response{
JSONRPC: "2.0",
ID: id,
Error: &rpcError{Code: code, Message: msg},
})
}
// handleCall dispatches a tools/call to the appropriate tool handler.
func (s *Server) handleCall(ctx context.Context, name string, args json.RawMessage) (json.RawMessage, error) {
switch name {
case "brain_query":
return s.brainQuery(ctx, args)
case "brain_write":
return s.brainWrite(ctx, args)
case "brain_index":
return s.brainIndex(ctx, args)
case "brain_tunnel":
return s.brainTunnel(ctx, args)
case "brain_ingest_raw":
return s.brainIngestRaw(ctx, args)
case "brain_ingest":
return s.brainIngest(ctx, args)
case "session_log":
return s.sessionLog(ctx, args)
case "brain_answer":
return s.brainAnswer(ctx, args)
case "brain_classify":
return s.brainClassify(ctx, args)
default:
return nil, fmt.Errorf("unknown tool: %s", name)
}
}