Changeset 0.18.0 (#79)

This commit is contained in:
2026-02-28 18:24:19 +00:00
parent 12e316c234
commit e4a943b03e
48 changed files with 3999 additions and 1398 deletions

261
server/memory/extractor.go Normal file
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package memory
import (
"context"
"encoding/json"
"fmt"
"log"
"strings"
"git.gobha.me/xcaliber/chat-switchboard/database"
"git.gobha.me/xcaliber/chat-switchboard/knowledge"
"git.gobha.me/xcaliber/chat-switchboard/models"
"git.gobha.me/xcaliber/chat-switchboard/providers"
"git.gobha.me/xcaliber/chat-switchboard/roles"
"git.gobha.me/xcaliber/chat-switchboard/store"
)
// defaultExtractionPrompt is used when the persona has no custom prompt.
const defaultExtractionPrompt = `You are a memory extraction assistant. Analyze the following conversation and extract memorable facts about the user.
Focus on:
- Personal preferences (language, tools, frameworks, communication style)
- Technical details (deployment stack, database choices, architecture patterns)
- Project context (project names, team size, deadlines, goals)
- Biographical facts (role, company, location, experience level)
Respond ONLY with a JSON array of extracted facts. Each fact must have:
- "key": short label (2-5 words, lowercase)
- "value": the detail/fact (1-2 sentences max)
- "confidence": 0.0-1.0 how certain you are
Example:
[
{"key": "preferred language", "value": "Go with Gin framework for backend services", "confidence": 0.95},
{"key": "deployment target", "value": "Kubernetes on AWS with PostgreSQL databases", "confidence": 0.8}
]
If no memorable facts are found, respond with an empty array: []`
// maxConversationChars limits the conversation text sent for extraction.
const maxConversationChars = 30000
// minMessagesForExtraction is the minimum new messages before extraction triggers.
const minMessagesForExtraction = 6
// extractedFact is the JSON structure returned by the utility model.
type extractedFact struct {
Key string `json:"key"`
Value string `json:"value"`
Confidence float64 `json:"confidence"`
}
// Extractor analyzes conversations and extracts memorable facts.
type Extractor struct {
stores store.Stores
roleResolver *roles.Resolver
embedder *knowledge.Embedder
}
// NewExtractor creates a new memory extraction service.
func NewExtractor(stores store.Stores, rr *roles.Resolver, embedder *knowledge.Embedder) *Extractor {
return &Extractor{stores: stores, roleResolver: rr, embedder: embedder}
}
// Extract analyzes a conversation and saves extracted facts as pending_review memories.
func (e *Extractor) Extract(ctx context.Context, channelID, userID, teamID, personaID string) error {
if e.stores.Memories == nil || e.stores.Messages == nil {
return fmt.Errorf("memory or message store not available")
}
// Check extraction log for last processed message
var lastMessageID string
row := database.DB.QueryRowContext(ctx,
database.Q(`SELECT last_message_id FROM memory_extraction_log WHERE channel_id = $1 AND user_id = $2`),
channelID, userID)
row.Scan(&lastMessageID) // ignore error — may not exist yet
// Load recent messages for this channel
messages, err := e.stores.Messages.ListForChannel(ctx, channelID, store.ListOptions{Limit: 200})
if err != nil {
return fmt.Errorf("load messages: %w", err)
}
// Filter to new messages only (messages come back newest-first)
var newMessages []models.Message
for i := len(messages) - 1; i >= 0; i-- {
if lastMessageID == "" || messages[i].ID > lastMessageID {
newMessages = append(newMessages, messages[i])
}
}
if len(newMessages) < minMessagesForExtraction {
return nil // not enough new content
}
// Build conversation text
var sb strings.Builder
for _, m := range newMessages {
role := m.Role
if role == "user" {
role = "User"
} else {
role = "Assistant"
}
line := fmt.Sprintf("[%s]: %s\n", role, m.Content)
if sb.Len()+len(line) > maxConversationChars {
break
}
sb.WriteString(line)
}
if sb.Len() < 200 {
return nil // too little content
}
// Get extraction prompt (persona-specific or default)
prompt := defaultExtractionPrompt
if personaID != "" && e.stores.Personas != nil {
persona, err := e.stores.Personas.GetByID(ctx, personaID)
if err == nil && persona.MemoryExtractionPrompt != nil && *persona.MemoryExtractionPrompt != "" {
prompt = *persona.MemoryExtractionPrompt
}
}
// Call utility model via role resolver
var tID *string
if teamID != "" {
tID = &teamID
}
apiMessages := []providers.Message{
{Role: "system", Content: prompt},
{Role: "user", Content: "Analyze this conversation and extract memorable facts:\n\n" + sb.String()},
}
result, err := e.roleResolver.Complete(ctx, "utility", userID, tID, apiMessages)
if err != nil {
return fmt.Errorf("extraction completion: %w", err)
}
// Parse response
facts, err := parseExtractionResponse(result.Content)
if err != nil {
log.Printf("⚠ memory extraction parse failed for channel %s: %v", channelID, err)
return nil // don't fail on parse errors
}
if len(facts) == 0 {
log.Printf("🧠 memory extraction: channel %s → 0 facts (nothing memorable)", channelID)
}
// Determine scope
scope := models.MemoryScopeUser
ownerID := userID
var memUserID *string
if personaID != "" {
scope = models.MemoryScopePersonaUser
ownerID = personaID
memUserID = &userID
}
// Save extracted facts
saved := 0
for _, f := range facts {
if f.Key == "" || f.Value == "" || f.Confidence < 0.3 {
continue
}
mem := &models.Memory{
ID: store.NewID(),
Scope: scope,
OwnerID: ownerID,
UserID: memUserID,
Key: f.Key,
Value: f.Value,
SourceChannelID: &channelID,
Confidence: f.Confidence,
Status: models.MemoryStatusPendingReview,
}
if err := e.stores.Memories.Upsert(ctx, mem); err != nil {
log.Printf("⚠ memory save failed: %v", err)
continue
}
// Embed if available
e.embedMemory(ctx, mem, userID, tID)
saved++
}
// Update extraction log
latestID := newMessages[len(newMessages)-1].ID
if database.IsSQLite() {
_, err = database.DB.ExecContext(ctx, `
INSERT INTO memory_extraction_log (id, channel_id, user_id, last_message_id, memory_count)
VALUES (?, ?, ?, ?, ?)
ON CONFLICT(channel_id, user_id) DO UPDATE SET
last_message_id = excluded.last_message_id,
extracted_at = datetime('now'),
memory_count = memory_extraction_log.memory_count + excluded.memory_count
`, store.NewID(), channelID, userID, latestID, saved)
} else {
_, err = database.DB.ExecContext(ctx, `
INSERT INTO memory_extraction_log (channel_id, user_id, last_message_id, memory_count)
VALUES ($1, $2, $3, $4)
ON CONFLICT(channel_id, user_id) DO UPDATE SET
last_message_id = EXCLUDED.last_message_id,
extracted_at = now(),
memory_count = memory_extraction_log.memory_count + EXCLUDED.memory_count
`, channelID, userID, latestID, saved)
}
if saved > 0 {
log.Printf("✅ memory extraction: channel %s → %d facts", channelID, saved)
}
return err
}
// embedMemory generates and stores an embedding vector for a memory.
func (e *Extractor) embedMemory(ctx context.Context, m *models.Memory, userID string, teamID *string) {
if e.embedder == nil || !e.embedder.IsConfigured(ctx) {
return
}
text := m.Key + ": " + m.Value
result, err := e.embedder.EmbedChunks(ctx, userID, teamID, []string{text})
if err != nil || len(result.Vectors) == 0 {
return
}
vecJSON, _ := json.Marshal(result.Vectors[0])
if database.IsSQLite() {
database.DB.ExecContext(ctx,
`UPDATE memories SET embedding = ? WHERE id = ?`,
string(vecJSON), m.ID)
} else {
database.DB.ExecContext(ctx,
`UPDATE memories SET embedding = $1::vector WHERE id = $2`,
string(vecJSON), m.ID)
}
}
// parseExtractionResponse parses the utility model's JSON response.
func parseExtractionResponse(content string) ([]extractedFact, error) {
content = strings.TrimSpace(content)
// Strip markdown code fences
if strings.HasPrefix(content, "```") {
lines := strings.Split(content, "\n")
if len(lines) > 2 {
lines = lines[1 : len(lines)-1]
content = strings.Join(lines, "\n")
}
}
var facts []extractedFact
if err := json.Unmarshal([]byte(content), &facts); err != nil {
return nil, fmt.Errorf("parse facts JSON: %w", err)
}
return facts, nil
}

197
server/memory/scanner.go Normal file
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package memory
import (
"context"
"log"
"sync"
"time"
"git.gobha.me/xcaliber/chat-switchboard/database"
"git.gobha.me/xcaliber/chat-switchboard/store"
)
// ScannerConfig holds tunable parameters for the background scanner.
type ScannerConfig struct {
Interval time.Duration // tick interval (default 10m)
Concurrency int // max parallel extractions (default 2)
}
// Scanner periodically finds conversations needing extraction.
type Scanner struct {
extractor *Extractor
stores store.Stores
cfg ScannerConfig
stopCh chan struct{}
wg sync.WaitGroup
inFlight sync.Map // channelID+userID → true
}
// NewScanner creates a background extraction scanner.
func NewScanner(ext *Extractor, stores store.Stores, cfg ScannerConfig) *Scanner {
if cfg.Interval <= 0 {
cfg.Interval = 10 * time.Minute
}
if cfg.Concurrency <= 0 {
cfg.Concurrency = 2
}
return &Scanner{
extractor: ext,
stores: stores,
cfg: cfg,
stopCh: make(chan struct{}),
}
}
// Start begins the background scanning loop.
func (s *Scanner) Start() {
s.wg.Add(1)
go func() {
defer s.wg.Done()
log.Printf("🧠 memory extraction scanner started (interval=%s, concurrency=%d)",
s.cfg.Interval, s.cfg.Concurrency)
ticker := time.NewTicker(s.cfg.Interval)
defer ticker.Stop()
for {
select {
case <-s.stopCh:
log.Println("🧠 memory extraction scanner stopped")
return
case <-ticker.C:
s.scan()
}
}
}()
}
// Stop gracefully shuts down the scanner.
func (s *Scanner) Stop() {
close(s.stopCh)
s.wg.Wait()
}
// candidate represents a conversation that may need extraction.
type candidate struct {
ChannelID string
UserID string
TeamID string
}
func (s *Scanner) scan() {
ctx := context.Background()
// Check global kill switch
if s.stores.GlobalConfig != nil {
val, err := s.stores.GlobalConfig.Get(ctx, "memory_extraction_enabled")
if err != nil || val == nil {
return // disabled or not configured
}
// val is a map; check the "value" key
if enabled, ok := val["value"].(bool); !ok || !enabled {
return
}
}
candidates, err := s.findCandidates(ctx)
if err != nil {
log.Printf("⚠ memory scanner: find candidates: %v", err)
return
}
if len(candidates) == 0 {
return
}
// Semaphore for concurrency control
sem := make(chan struct{}, s.cfg.Concurrency)
var wg sync.WaitGroup
for _, c := range candidates {
key := c.ChannelID + ":" + c.UserID
if _, loaded := s.inFlight.LoadOrStore(key, true); loaded {
continue // already in progress
}
sem <- struct{}{} // acquire
wg.Add(1)
go func(cand candidate) {
defer wg.Done()
defer func() { <-sem }() // release
defer s.inFlight.Delete(cand.ChannelID + ":" + cand.UserID)
extractCtx, cancel := context.WithTimeout(ctx, 2*time.Minute)
defer cancel()
if err := s.extractor.Extract(extractCtx, cand.ChannelID, cand.UserID, cand.TeamID, ""); err != nil {
log.Printf("⚠ memory extraction failed: channel=%s user=%s: %v",
cand.ChannelID, cand.UserID, err)
}
}(c)
}
wg.Wait()
}
// findCandidates queries for channels with enough new activity since last extraction.
func (s *Scanner) findCandidates(ctx context.Context) ([]candidate, error) {
db := database.DB
if db == nil {
return nil, nil
}
var query string
if database.IsSQLite() {
query = `
SELECT c.id, c.created_by, COALESCE(cu.team_id, '')
FROM channels c
LEFT JOIN channel_users cu ON cu.channel_id = c.id AND cu.user_id = c.created_by
LEFT JOIN memory_extraction_log mel ON mel.channel_id = c.id AND mel.user_id = c.created_by
WHERE c.created_by IS NOT NULL
AND (
SELECT COUNT(*) FROM messages m
WHERE m.channel_id = c.id
AND (mel.last_message_id IS NULL OR m.id > mel.last_message_id)
) >= 8
AND (
SELECT MAX(m2.created_at) FROM messages m2 WHERE m2.channel_id = c.id
) < datetime('now', '-5 minutes')
LIMIT 20
`
} else {
query = `
SELECT c.id, c.created_by, COALESCE(cu.team_id, '')
FROM channels c
LEFT JOIN channel_users cu ON cu.channel_id = c.id AND cu.user_id = c.created_by
LEFT JOIN memory_extraction_log mel ON mel.channel_id = c.id AND mel.user_id = c.created_by
WHERE c.created_by IS NOT NULL
AND (
SELECT COUNT(*) FROM messages m
WHERE m.channel_id = c.id
AND (mel.last_message_id IS NULL OR m.id::text > mel.last_message_id::text)
) >= 8
AND (
SELECT MAX(m2.created_at) FROM messages m2 WHERE m2.channel_id = c.id
) < now() - interval '5 minutes'
LIMIT 20
`
}
rows, err := db.QueryContext(ctx, query)
if err != nil {
return nil, err
}
defer rows.Close()
var candidates []candidate
for rows.Next() {
var c candidate
if err := rows.Scan(&c.ChannelID, &c.UserID, &c.TeamID); err != nil {
continue
}
candidates = append(candidates, c)
}
return candidates, rows.Err()
}