mirror of
https://github.com/lukaszraczylo/claude-mnemonic.git
synced 2026-06-05 23:03:55 +00:00
f79782a008
* Resolves issue #13 - Switched model to bge-small-en-v1.5 - Added lazy re-embedding - Added model version tracking per vector - Added conversion of vectors to the new model * Add lfs support to the workflow. * Implements importance scoring with decay + voting #6 * Resolves issue #5 by marking observations as superseeded and scheduled for deletion * Implement pattern detection #7 * Improve injections and observations accuracy - Session start: Recent observations for project context (recency-based) - User prompt: Semantically relevant observations (similarity-based with threshold) * Added two stage retrieval with bi and cross encoder #8 * Implement query expansion and reformulation #9 * Knowledge graph and relationships ( resolves #4 ) - File Overlap Detection: Detects relationships when observations modify/read the same files - Concept Overlap Detection: Detects relationships based on shared semantic concepts - Type Progression Detection: Infers relationships from natural observation type progressions (e.g., discovery → bugfix = "fixes") - Temporal Proximity Detection: Detects relationships between observations in the same session within 5 minutes - Narrative Mention Detection: Detects explicit relationship language in narratives (e.g., "fixes", "depends on", "supersedes") * Add visualisation of the relations to the dashboard. * fixup! Add visualisation of the relations to the dashboard. * Update documentation with new settings and screenshots.
341 lines
9.5 KiB
Go
341 lines
9.5 KiB
Go
// Package sqlitevec provides sqlite-vec based vector database integration for claude-mnemonic.
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package sqlitevec
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import (
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"context"
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"fmt"
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"github.com/lukaszraczylo/claude-mnemonic/pkg/models"
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"github.com/rs/zerolog/log"
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)
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// Sync provides synchronization between SQLite data and vector embeddings.
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type Sync struct {
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client *Client
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}
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// NewSync creates a new sync service.
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func NewSync(client *Client) *Sync {
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return &Sync{client: client}
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}
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// SyncObservation syncs a single observation to the vector store.
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func (s *Sync) SyncObservation(ctx context.Context, obs *models.Observation) error {
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docs := s.formatObservationDocs(obs)
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if len(docs) == 0 {
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return nil
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}
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if err := s.client.AddDocuments(ctx, docs); err != nil {
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return fmt.Errorf("add observation docs: %w", err)
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}
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log.Debug().
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Int64("observationId", obs.ID).
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Int("docCount", len(docs)).
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Msg("Synced observation to sqlite-vec")
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return nil
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}
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// formatObservationDocs formats an observation into vector documents.
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// Each semantic field becomes a separate vector document (granular approach).
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func (s *Sync) formatObservationDocs(obs *models.Observation) []Document {
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docs := make([]Document, 0, len(obs.Facts)+2)
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// Determine scope for metadata
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scope := string(obs.Scope)
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if scope == "" {
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scope = "project"
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}
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baseMetadata := map[string]any{
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"sqlite_id": obs.ID,
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"doc_type": "observation",
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"sdk_session_id": obs.SDKSessionID,
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"project": obs.Project,
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"scope": scope,
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"created_at_epoch": obs.CreatedAtEpoch,
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"type": string(obs.Type),
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}
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if obs.Title.Valid {
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baseMetadata["title"] = obs.Title.String
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}
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if obs.Subtitle.Valid {
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baseMetadata["subtitle"] = obs.Subtitle.String
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}
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if len(obs.Concepts) > 0 {
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baseMetadata["concepts"] = joinStrings(obs.Concepts, ",")
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}
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if len(obs.FilesRead) > 0 {
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baseMetadata["files_read"] = joinStrings(obs.FilesRead, ",")
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}
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if len(obs.FilesModified) > 0 {
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baseMetadata["files_modified"] = joinStrings(obs.FilesModified, ",")
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}
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// Narrative as separate document
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if obs.Narrative.Valid && obs.Narrative.String != "" {
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docs = append(docs, Document{
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ID: fmt.Sprintf("obs_%d_narrative", obs.ID),
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Content: obs.Narrative.String,
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Metadata: copyMetadata(baseMetadata, "field_type", "narrative"),
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})
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}
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// Each fact as separate document
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for i, fact := range obs.Facts {
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docs = append(docs, Document{
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ID: fmt.Sprintf("obs_%d_fact_%d", obs.ID, i),
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Content: fact,
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Metadata: copyMetadataMulti(baseMetadata, map[string]any{
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"field_type": "fact",
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"fact_index": i,
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}),
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})
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}
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return docs
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}
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// SyncSummary syncs a single session summary to the vector store.
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func (s *Sync) SyncSummary(ctx context.Context, summary *models.SessionSummary) error {
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docs := s.formatSummaryDocs(summary)
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if len(docs) == 0 {
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return nil
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}
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if err := s.client.AddDocuments(ctx, docs); err != nil {
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return fmt.Errorf("add summary docs: %w", err)
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}
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log.Debug().
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Int64("summaryId", summary.ID).
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Int("docCount", len(docs)).
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Msg("Synced summary to sqlite-vec")
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return nil
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}
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// formatSummaryDocs formats a session summary into vector documents.
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func (s *Sync) formatSummaryDocs(summary *models.SessionSummary) []Document {
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docs := make([]Document, 0, 6)
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baseMetadata := map[string]any{
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"sqlite_id": summary.ID,
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"doc_type": "session_summary",
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"sdk_session_id": summary.SDKSessionID,
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"project": summary.Project,
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"scope": "", // Summaries don't have scope
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"created_at_epoch": summary.CreatedAtEpoch,
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}
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if summary.PromptNumber.Valid {
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baseMetadata["prompt_number"] = summary.PromptNumber.Int64
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}
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// Each field as separate document
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fields := []struct {
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name string
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value string
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valid bool
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}{
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{"request", summary.Request.String, summary.Request.Valid},
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{"investigated", summary.Investigated.String, summary.Investigated.Valid},
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{"learned", summary.Learned.String, summary.Learned.Valid},
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{"completed", summary.Completed.String, summary.Completed.Valid},
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{"next_steps", summary.NextSteps.String, summary.NextSteps.Valid},
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{"notes", summary.Notes.String, summary.Notes.Valid},
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}
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for _, field := range fields {
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if field.valid && field.value != "" {
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docs = append(docs, Document{
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ID: fmt.Sprintf("summary_%d_%s", summary.ID, field.name),
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Content: field.value,
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Metadata: copyMetadata(baseMetadata, "field_type", field.name),
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})
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}
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}
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return docs
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}
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// SyncUserPrompt syncs a single user prompt to the vector store.
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func (s *Sync) SyncUserPrompt(ctx context.Context, prompt *models.UserPromptWithSession) error {
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doc := Document{
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ID: fmt.Sprintf("prompt_%d", prompt.ID),
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Content: prompt.PromptText,
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Metadata: map[string]any{
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"sqlite_id": prompt.ID,
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"doc_type": "user_prompt",
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"sdk_session_id": prompt.SDKSessionID,
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"project": prompt.Project,
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"scope": "", // Prompts don't have scope
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"created_at_epoch": prompt.CreatedAtEpoch,
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"prompt_number": prompt.PromptNumber,
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"field_type": "prompt",
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},
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}
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if err := s.client.AddDocuments(ctx, []Document{doc}); err != nil {
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return fmt.Errorf("add prompt doc: %w", err)
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}
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log.Debug().
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Int64("promptId", prompt.ID).
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Msg("Synced user prompt to sqlite-vec")
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return nil
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}
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// DeleteObservations removes observation documents from the vector store.
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func (s *Sync) DeleteObservations(ctx context.Context, observationIDs []int64) error {
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if len(observationIDs) == 0 {
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return nil
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}
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// Generate all possible document IDs for these observations
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// Pattern: obs_{id}_narrative, obs_{id}_fact_{0..n}
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const maxFactsPerObs = 20
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ids := make([]string, 0, len(observationIDs)*(maxFactsPerObs+1))
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for _, obsID := range observationIDs {
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ids = append(ids, fmt.Sprintf("obs_%d_narrative", obsID))
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for i := 0; i < maxFactsPerObs; i++ {
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ids = append(ids, fmt.Sprintf("obs_%d_fact_%d", obsID, i))
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}
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}
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if err := s.client.DeleteDocuments(ctx, ids); err != nil {
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return fmt.Errorf("delete observation docs: %w", err)
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}
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log.Debug().
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Int("observationCount", len(observationIDs)).
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Msg("Deleted observations from sqlite-vec")
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return nil
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}
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// DeleteUserPrompts removes user prompt documents from the vector store.
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func (s *Sync) DeleteUserPrompts(ctx context.Context, promptIDs []int64) error {
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if len(promptIDs) == 0 {
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return nil
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}
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ids := make([]string, len(promptIDs))
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for i, promptID := range promptIDs {
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ids[i] = fmt.Sprintf("prompt_%d", promptID)
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}
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if err := s.client.DeleteDocuments(ctx, ids); err != nil {
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return fmt.Errorf("delete prompt docs: %w", err)
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}
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log.Debug().
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Int("promptCount", len(promptIDs)).
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Msg("Deleted user prompts from sqlite-vec")
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return nil
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}
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// SyncPattern syncs a single pattern to the vector store.
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func (s *Sync) SyncPattern(ctx context.Context, pattern *models.Pattern) error {
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docs := s.formatPatternDocs(pattern)
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if len(docs) == 0 {
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return nil
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}
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if err := s.client.AddDocuments(ctx, docs); err != nil {
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return fmt.Errorf("add pattern docs: %w", err)
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}
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log.Debug().
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Int64("patternId", pattern.ID).
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Int("docCount", len(docs)).
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Msg("Synced pattern to sqlite-vec")
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return nil
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}
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// formatPatternDocs formats a pattern into vector documents.
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func (s *Sync) formatPatternDocs(pattern *models.Pattern) []Document {
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docs := make([]Document, 0, 3)
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baseMetadata := map[string]any{
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"sqlite_id": pattern.ID,
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"doc_type": "pattern",
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"pattern_type": string(pattern.Type),
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"status": string(pattern.Status),
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"scope": "global", // Patterns are always global
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"frequency": pattern.Frequency,
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"confidence": pattern.Confidence,
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"created_at_epoch": pattern.CreatedAtEpoch,
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}
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if len(pattern.Signature) > 0 {
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baseMetadata["signature"] = joinStrings(pattern.Signature, ",")
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}
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if len(pattern.Projects) > 0 {
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baseMetadata["projects"] = joinStrings(pattern.Projects, ",")
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}
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// Pattern name as document
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if pattern.Name != "" {
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docs = append(docs, Document{
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ID: fmt.Sprintf("pattern_%d_name", pattern.ID),
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Content: pattern.Name,
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Metadata: copyMetadata(baseMetadata, "field_type", "name"),
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})
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}
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// Pattern description as document
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if pattern.Description.Valid && pattern.Description.String != "" {
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docs = append(docs, Document{
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ID: fmt.Sprintf("pattern_%d_description", pattern.ID),
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Content: pattern.Description.String,
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Metadata: copyMetadata(baseMetadata, "field_type", "description"),
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})
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}
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// Pattern recommendation as document
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if pattern.Recommendation.Valid && pattern.Recommendation.String != "" {
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docs = append(docs, Document{
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ID: fmt.Sprintf("pattern_%d_recommendation", pattern.ID),
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Content: pattern.Recommendation.String,
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Metadata: copyMetadata(baseMetadata, "field_type", "recommendation"),
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})
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}
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return docs
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}
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// DeletePatterns removes pattern documents from the vector store.
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func (s *Sync) DeletePatterns(ctx context.Context, patternIDs []int64) error {
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if len(patternIDs) == 0 {
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return nil
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}
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// Generate all possible document IDs for these patterns
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// Pattern: pattern_{id}_name, pattern_{id}_description, pattern_{id}_recommendation
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ids := make([]string, 0, len(patternIDs)*3)
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for _, patternID := range patternIDs {
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ids = append(ids, fmt.Sprintf("pattern_%d_name", patternID))
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ids = append(ids, fmt.Sprintf("pattern_%d_description", patternID))
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ids = append(ids, fmt.Sprintf("pattern_%d_recommendation", patternID))
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}
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if err := s.client.DeleteDocuments(ctx, ids); err != nil {
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return fmt.Errorf("delete pattern docs: %w", err)
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}
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log.Debug().
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Int("patternCount", len(patternIDs)).
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Msg("Deleted patterns from sqlite-vec")
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return nil
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}
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