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gitlore/SPEC.md
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2026-01-20 13:11:40 -05:00

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# GitLab Knowledge Engine - Spec Document
## Executive Summary
A self-hosted tool to extract, index, and semantically search 2+ years of GitLab data (issues, MRs, comments/notes, and MR file-change links) from 2 main repositories (~10K items). The MVP delivers semantic search as a foundational capability that enables future specialized views (file history, personal tracking, person context). Commit-level indexing is explicitly post-MVP.
---
## Discovery Summary
### Pain Points Identified
1. **Knowledge discovery** - Tribal knowledge buried in old MRs/issues that nobody can find
2. **Decision traceability** - Hard to find *why* decisions were made; context scattered across issue comments and MR discussions
### Constraints
| Constraint | Detail |
|------------|--------|
| Hosting | Self-hosted only, no external APIs |
| Compute | Local dev machine (M-series Mac assumed) |
| GitLab Access | Self-hosted instance, PAT access, no webhooks (could request) |
| Build Method | AI agents will implement; user is TypeScript expert for review |
### Target Use Cases (Priority Order)
1. **MVP: Semantic Search** - "Find discussions about authentication redesign"
2. **Future: File/Feature History** - "What decisions were made about src/auth/login.ts?"
3. **Future: Personal Tracking** - "What am I assigned to or mentioned in?"
4. **Future: Person Context** - "What's @johndoe's background in this project?"
---
## Architecture Overview
```
┌─────────────────────────────────────────────────────────────────┐
│ GitLab API │
│ (Issues, MRs, Notes) │
└─────────────────────────────────────────────────────────────────┘
(Commit-level indexing explicitly post-MVP)
┌─────────────────────────────────────────────────────────────────┐
│ Data Ingestion Layer │
│ - Incremental sync (PAT-based polling) │
│ - Rate limiting / backoff │
│ - Raw JSON storage for replay │
│ - Dependent resource fetching (notes, MR changes) │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ Data Processing Layer │
│ - Normalize artifacts to unified schema │
│ - Extract searchable documents (canonical text + metadata) │
│ - Content hashing for change detection │
│ - Build relationship graph (issue↔MR↔note↔file) │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ Storage Layer │
│ - SQLite + sqlite-vss + FTS5 (hybrid search) │
│ - Structured metadata in relational tables │
│ - Vector embeddings for semantic search │
│ - Full-text index for lexical search fallback │
└─────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────┐
│ Query Interface │
│ - CLI for human testing │
│ - JSON API for AI agent testing │
│ - Semantic search with filters (author, date, type, label) │
└─────────────────────────────────────────────────────────────────┘
```
### Technology Choices
| Component | Recommendation | Rationale |
|-----------|---------------|-----------|
| Language | TypeScript/Node.js | User expertise, good GitLab libs, AI agent friendly |
| Database | SQLite + sqlite-vss | Zero-config, portable, vector search built-in |
| Embeddings | Ollama + nomic-embed-text | Self-hosted, runs well on Apple Silicon, 768-dim vectors |
| CLI Framework | Commander.js or oclif | Standard, well-documented |
### Alternative Considered: Postgres + pgvector
- Pros: More scalable, better for production multi-user
- Cons: Requires running Postgres, heavier setup
- Decision: Start with SQLite for simplicity; migration path exists if needed
---
## Checkpoint Structure
Each checkpoint is a **testable milestone** where a human can validate the system works before proceeding.
### Checkpoint 0: Project Setup
**Deliverable:** Scaffolded project with GitLab API connection verified
**Tests:**
1. Run `gitlab-engine auth-test` → returns authenticated user info
2. Run `gitlab-engine doctor` → verifies:
- Can reach GitLab baseUrl
- PAT is present and can read configured projects
- SQLite opens DB and migrations apply
- Ollama reachable OR embedding disabled with clear warning
**Scope:**
- Project structure (TypeScript, ESLint, Vitest)
- GitLab API client with PAT authentication
- Environment and project configuration
- Basic CLI scaffold with `auth-test` command
- `doctor` command for environment verification
- Projects table and initial sync
**Configuration (MVP):**
```json
// gitlab-engine.config.json
{
"gitlab": {
"baseUrl": "https://gitlab.example.com",
"tokenEnvVar": "GITLAB_TOKEN"
},
"projects": [
{ "path": "group/project-one" },
{ "path": "group/project-two" }
],
"embedding": {
"provider": "ollama",
"model": "nomic-embed-text",
"baseUrl": "http://localhost:11434"
}
}
```
**DB Runtime Defaults (Checkpoint 0):**
- On every connection:
- `PRAGMA journal_mode=WAL;`
- `PRAGMA foreign_keys=ON;`
**Schema (Checkpoint 0):**
```sql
-- Projects table (configured targets)
CREATE TABLE projects (
id INTEGER PRIMARY KEY,
gitlab_project_id INTEGER UNIQUE NOT NULL,
path_with_namespace TEXT NOT NULL,
default_branch TEXT,
web_url TEXT,
created_at INTEGER,
updated_at INTEGER,
raw_payload_id INTEGER REFERENCES raw_payloads(id)
);
CREATE INDEX idx_projects_path ON projects(path_with_namespace);
-- Sync tracking for reliability
CREATE TABLE sync_runs (
id INTEGER PRIMARY KEY,
started_at INTEGER NOT NULL,
finished_at INTEGER,
status TEXT NOT NULL, -- 'running' | 'succeeded' | 'failed'
command TEXT NOT NULL, -- 'ingest issues' | 'sync' | etc.
error TEXT
);
-- Sync cursors for primary resources only
-- Notes and MR changes are dependent resources (fetched via parent updates)
CREATE TABLE sync_cursors (
project_id INTEGER NOT NULL REFERENCES projects(id),
resource_type TEXT NOT NULL, -- 'issues' | 'merge_requests'
updated_at_cursor INTEGER, -- last fully processed updated_at (ms epoch)
tie_breaker_id INTEGER, -- last fully processed gitlab_id (for stable ordering)
PRIMARY KEY(project_id, resource_type)
);
-- Raw payload storage (decoupled from entity tables)
CREATE TABLE raw_payloads (
id INTEGER PRIMARY KEY,
source TEXT NOT NULL, -- 'gitlab'
resource_type TEXT NOT NULL, -- 'project' | 'issue' | 'mr' | 'note'
gitlab_id INTEGER NOT NULL,
fetched_at INTEGER NOT NULL,
json TEXT NOT NULL
);
CREATE INDEX idx_raw_payloads_lookup ON raw_payloads(resource_type, gitlab_id);
```
---
### Checkpoint 1: Issue Ingestion
**Deliverable:** All issues from target repos stored locally
**Test:** Run `gitlab-engine ingest --type=issues` → count matches GitLab; run `gitlab-engine list issues --limit=10` → displays issues correctly
**Scope:**
- Issue fetcher with pagination handling
- Raw JSON storage in raw_payloads table
- Normalized issue schema in SQLite
- Labels ingestion derived from issue payload:
- Always persist label names from `labels: string[]`
- Optionally request `with_labels_details=true` to capture color/description when available
- Incremental sync support (run tracking + per-project cursor)
- Basic list/count CLI commands
**Reliability/Idempotency Rules:**
- Every ingest/sync creates a `sync_runs` row
- Single-flight: refuse to start if an existing run is `running` (unless `--force`)
- Cursor advances only after successful transaction commit per page/batch
- Ordering: `updated_at ASC`, tie-breaker `gitlab_id ASC`
- Use explicit transactions for batch inserts
**Schema Preview:**
```sql
CREATE TABLE issues (
id INTEGER PRIMARY KEY,
gitlab_id INTEGER UNIQUE NOT NULL,
project_id INTEGER NOT NULL REFERENCES projects(id),
iid INTEGER NOT NULL,
title TEXT,
description TEXT,
state TEXT,
author_username TEXT,
created_at INTEGER,
updated_at INTEGER,
web_url TEXT,
raw_payload_id INTEGER REFERENCES raw_payloads(id)
);
CREATE INDEX idx_issues_project_updated ON issues(project_id, updated_at);
CREATE INDEX idx_issues_author ON issues(author_username);
-- Labels are derived from issue payloads (string array)
-- Uniqueness is (project_id, name) since gitlab_id isn't always available
CREATE TABLE labels (
id INTEGER PRIMARY KEY,
gitlab_id INTEGER, -- optional (only if available)
project_id INTEGER NOT NULL REFERENCES projects(id),
name TEXT NOT NULL,
color TEXT,
description TEXT
);
CREATE UNIQUE INDEX uq_labels_project_name ON labels(project_id, name);
CREATE INDEX idx_labels_name ON labels(name);
CREATE TABLE issue_labels (
issue_id INTEGER REFERENCES issues(id),
label_id INTEGER REFERENCES labels(id),
PRIMARY KEY(issue_id, label_id)
);
CREATE INDEX idx_issue_labels_label ON issue_labels(label_id);
```
---
### Checkpoint 2: MR + Comments + File Links Ingestion
**Deliverable:** All MRs, discussion threads, and file-change links stored locally
**Test:** Run `gitlab-engine ingest --type=merge_requests` → count matches; run `gitlab-engine show mr 1234` → displays MR with comments and files changed
**Scope:**
- MR fetcher with pagination
- Notes fetcher (issue notes + MR notes) as a dependent resource:
- During initial ingest: fetch notes for every issue/MR
- During sync: refetch notes only for issues/MRs updated since cursor
- MR changes/diffs fetcher as a dependent resource:
- During initial ingest: fetch changes for every MR
- During sync: refetch changes only for MRs updated since cursor
- Relationship linking (note → parent issue/MR via foreign keys, MR → files)
- Extended CLI commands for MR display
**Schema Additions:**
```sql
CREATE TABLE merge_requests (
id INTEGER PRIMARY KEY,
gitlab_id INTEGER UNIQUE NOT NULL,
project_id INTEGER NOT NULL REFERENCES projects(id),
iid INTEGER NOT NULL,
title TEXT,
description TEXT,
state TEXT,
author_username TEXT,
source_branch TEXT,
target_branch TEXT,
created_at INTEGER,
updated_at INTEGER,
merged_at INTEGER,
web_url TEXT,
raw_payload_id INTEGER REFERENCES raw_payloads(id)
);
CREATE INDEX idx_mrs_project_updated ON merge_requests(project_id, updated_at);
CREATE INDEX idx_mrs_author ON merge_requests(author_username);
-- Notes with explicit parent foreign keys for referential integrity
CREATE TABLE notes (
id INTEGER PRIMARY KEY,
gitlab_id INTEGER UNIQUE NOT NULL,
project_id INTEGER NOT NULL REFERENCES projects(id),
issue_id INTEGER REFERENCES issues(id),
merge_request_id INTEGER REFERENCES merge_requests(id),
noteable_type TEXT NOT NULL, -- 'Issue' | 'MergeRequest'
noteable_iid INTEGER NOT NULL, -- parent IID (from API path)
author_username TEXT,
body TEXT,
created_at INTEGER,
updated_at INTEGER,
system BOOLEAN,
raw_payload_id INTEGER REFERENCES raw_payloads(id),
-- Exactly one parent FK must be set
CHECK (
(noteable_type='Issue' AND issue_id IS NOT NULL AND merge_request_id IS NULL) OR
(noteable_type='MergeRequest' AND merge_request_id IS NOT NULL AND issue_id IS NULL)
)
);
CREATE INDEX idx_notes_issue ON notes(issue_id);
CREATE INDEX idx_notes_mr ON notes(merge_request_id);
CREATE INDEX idx_notes_author ON notes(author_username);
-- File linkage for "what MRs touched this file?" queries (with rename support)
CREATE TABLE mr_files (
id INTEGER PRIMARY KEY,
merge_request_id INTEGER REFERENCES merge_requests(id),
old_path TEXT,
new_path TEXT,
new_file BOOLEAN,
deleted_file BOOLEAN,
renamed_file BOOLEAN,
UNIQUE(merge_request_id, old_path, new_path)
);
CREATE INDEX idx_mr_files_old_path ON mr_files(old_path);
CREATE INDEX idx_mr_files_new_path ON mr_files(new_path);
-- MR labels (reuse same labels table)
CREATE TABLE mr_labels (
merge_request_id INTEGER REFERENCES merge_requests(id),
label_id INTEGER REFERENCES labels(id),
PRIMARY KEY(merge_request_id, label_id)
);
CREATE INDEX idx_mr_labels_label ON mr_labels(label_id);
```
---
### Checkpoint 3: Embedding Generation
**Deliverable:** Vector embeddings generated for all text content
**Test:** Run `gitlab-engine embed --all` → progress indicator; run `gitlab-engine stats` → shows embedding coverage percentage
**Scope:**
- Ollama integration (nomic-embed-text model)
- Embedding generation pipeline (batch processing)
- Vector storage in SQLite (sqlite-vss extension)
- Progress tracking and resumability
- Document extraction layer:
- Canonical "search documents" derived from issues/MRs/notes
- Stable content hashing for change detection (SHA-256 of content_text)
- Single embedding per document (chunking deferred to post-MVP)
- Denormalized metadata for fast filtering (author, labels, dates)
- Fast label filtering via `document_labels` join table
**Schema Additions:**
```sql
-- Unified searchable documents (derived from issues/MRs/notes)
CREATE TABLE documents (
id INTEGER PRIMARY KEY,
source_type TEXT NOT NULL, -- 'issue' | 'merge_request' | 'note'
source_id INTEGER NOT NULL, -- local DB id in the source table
project_id INTEGER NOT NULL REFERENCES projects(id),
author_username TEXT,
label_names TEXT, -- JSON array (display/debug only)
created_at INTEGER,
updated_at INTEGER,
url TEXT,
title TEXT, -- null for notes
content_text TEXT NOT NULL, -- canonical text for embedding/snippets
content_hash TEXT NOT NULL, -- SHA-256 for change detection
UNIQUE(source_type, source_id)
);
CREATE INDEX idx_documents_project_updated ON documents(project_id, updated_at);
CREATE INDEX idx_documents_author ON documents(author_username);
CREATE INDEX idx_documents_source ON documents(source_type, source_id);
-- Fast label filtering for documents (indexed exact-match)
CREATE TABLE document_labels (
document_id INTEGER NOT NULL REFERENCES documents(id),
label_name TEXT NOT NULL,
PRIMARY KEY(document_id, label_name)
);
CREATE INDEX idx_document_labels_label ON document_labels(label_name);
-- sqlite-vss virtual table
-- Storage rule: embeddings.rowid = documents.id
CREATE VIRTUAL TABLE embeddings USING vss0(
embedding(768)
);
-- Embedding provenance + change detection
-- document_id is PRIMARY KEY and equals embeddings.rowid
CREATE TABLE embedding_metadata (
document_id INTEGER PRIMARY KEY REFERENCES documents(id),
model TEXT NOT NULL, -- 'nomic-embed-text'
dims INTEGER NOT NULL, -- 768
content_hash TEXT NOT NULL, -- copied from documents.content_hash
created_at INTEGER NOT NULL
);
```
**Storage Rule (MVP):**
- Insert embedding with `rowid = documents.id`
- Upsert `embedding_metadata` by `document_id`
- This alignment simplifies joins and eliminates rowid mapping fragility
**Document Extraction Rules:**
- Issue → title + "\n\n" + description
- MR → title + "\n\n" + description
- Note → body (skip system notes unless they contain meaningful content)
---
### Checkpoint 4: Semantic Search
**Deliverable:** Working semantic search across all indexed content
**Tests:**
1. Run `gitlab-engine search "authentication redesign"` → returns ranked results with snippets
2. Golden queries: curated list of 10 queries with expected result *containment* (e.g., "at least one of these 3 known URLs appears in top 10")
3. `gitlab-engine search "..." --json` validates against JSON schema (stable fields present)
**Scope:**
- Hybrid retrieval:
- Vector recall (sqlite-vss) + FTS lexical recall (fts5)
- Merge + rerank results using Reciprocal Rank Fusion (RRF)
- Result ranking and scoring (document-level)
- Search filters: `--type=issue|mr|note`, `--author=username`, `--after=date`, `--label=name`
- Label filtering operates on `document_labels` (indexed, exact-match)
- Output formatting: ranked list with title, snippet, score, URL
- JSON output mode for AI agent consumption
**Schema Additions:**
```sql
-- Full-text search for hybrid retrieval
CREATE VIRTUAL TABLE documents_fts USING fts5(
title,
content_text,
content='documents',
content_rowid='id'
);
-- Triggers to keep FTS in sync
CREATE TRIGGER documents_ai AFTER INSERT ON documents BEGIN
INSERT INTO documents_fts(rowid, title, content_text)
VALUES (new.id, new.title, new.content_text);
END;
CREATE TRIGGER documents_ad AFTER DELETE ON documents BEGIN
INSERT INTO documents_fts(documents_fts, rowid, title, content_text)
VALUES('delete', old.id, old.title, old.content_text);
END;
CREATE TRIGGER documents_au AFTER UPDATE ON documents BEGIN
INSERT INTO documents_fts(documents_fts, rowid, title, content_text)
VALUES('delete', old.id, old.title, old.content_text);
INSERT INTO documents_fts(rowid, title, content_text)
VALUES (new.id, new.title, new.content_text);
END;
```
**Hybrid Search Algorithm (MVP) - Reciprocal Rank Fusion:**
1. Query both vector index (top 50) and FTS5 (top 50)
2. Merge results by document_id
3. Combine with Reciprocal Rank Fusion (RRF):
- For each retriever list, assign ranks (1..N)
- `rrf_score = Σ 1 / (k + rank)` with k=60 (tunable)
- RRF is simpler than weighted sums and doesn't require score normalization
4. Apply filters (type, author, date, label)
5. Return top K
**Why RRF over Weighted Sums:**
- FTS5 BM25 scores and vector distances use different scales
- Weighted sums (`0.7 * vector + 0.3 * fts`) require careful normalization
- RRF operates on ranks, not scores, making it robust to scale differences
- Well-established in information retrieval literature
**CLI Interface:**
```bash
# Basic semantic search
gitlab-engine search "why did we choose Redis"
# Pure FTS search (fallback if embeddings unavailable)
gitlab-engine search "redis" --mode=lexical
# Filtered search
gitlab-engine search "authentication" --type=mr --after=2024-01-01
# Filter by label
gitlab-engine search "performance" --label=bug --label=critical
# JSON output for programmatic use
gitlab-engine search "payment processing" --json
```
---
### Checkpoint 5: Incremental Sync
**Deliverable:** Efficient ongoing synchronization with GitLab
**Test:** Make a change in GitLab; run `gitlab-engine sync` → only fetches changed items; verify change appears in search
**Scope:**
- Delta sync based on stable cursor (updated_at + tie-breaker id)
- Dependent resources sync strategy (notes, MR changes)
- Webhook handler (optional, if webhook access granted)
- Re-embedding based on content_hash change (documents.content_hash != embedding_metadata.content_hash)
- Sync status reporting
**Correctness Rules (MVP):**
1. Fetch pages ordered by `updated_at ASC`, within identical timestamps advance by `gitlab_id ASC`
2. Cursor advances only after successful DB commit for that page
3. Dependent resources:
- For each updated issue/MR, refetch its notes (sorted by `updated_at`)
- For each updated MR, refetch its file changes
4. A document is queued for embedding iff `documents.content_hash != embedding_metadata.content_hash`
5. Sync run is marked 'failed' with error message if any page fails (can resume from cursor)
**Why Dependent Resource Model:**
- GitLab Notes API doesn't provide a clean global `updated_after` stream
- Notes are listed per-issue or per-MR, not as a top-level resource
- Treating notes as dependent resources (refetch when parent updates) is simpler and more correct
- Same applies to MR changes/diffs
**CLI Commands:**
```bash
# Full sync (respects cursors, only fetches new/updated)
gitlab-engine sync
# Force full re-sync (resets cursors)
gitlab-engine sync --full
# Override stale 'running' run after operator review
gitlab-engine sync --force
# Show sync status
gitlab-engine sync-status
```
---
## Future Checkpoints (Post-MVP)
### Checkpoint 6: File/Feature History View
- Map commits to MRs to discussions
- Query: "Show decision history for src/auth/login.ts"
- Ship `gitlab-engine file-history <path>` as a first-class feature here
- This command is deferred from MVP to sharpen checkpoint focus
### Checkpoint 7: Personal Dashboard
- Filter by assigned/mentioned
- Integrate with existing gitlab-inbox tool
### Checkpoint 8: Person Context
- Aggregate contributions by author
- Expertise inference from activity
### Checkpoint 9: Decision Graph
- Extract decisions from discussions (LLM-assisted)
- Visualize decision relationships
---
## Verification Strategy
Each checkpoint includes:
1. **Automated tests** - Unit tests for data transformations, integration tests for API calls
2. **CLI smoke tests** - Manual commands with expected outputs documented
3. **Data integrity checks** - Count verification against GitLab, schema validation
4. **Search quality tests** - Known queries with expected results (for Checkpoint 4+)
---
## Risk Mitigation
| Risk | Mitigation |
|------|------------|
| GitLab rate limiting | Exponential backoff, respect Retry-After headers, incremental sync |
| Embedding model quality | Start with nomic-embed-text; architecture allows model swap |
| SQLite scale limits | Monitor performance; Postgres migration path documented |
| Stale data | Incremental sync with change detection |
| Mid-sync failures | Cursor-based resumption, sync_runs audit trail |
| Search quality | Hybrid (vector + FTS5) retrieval with RRF, golden query test suite |
| Concurrent sync corruption | Single-flight protection (refuse if existing run is `running`) |
**SQLite Performance Defaults (MVP):**
- Enable `PRAGMA journal_mode=WAL;` on every connection
- Enable `PRAGMA foreign_keys=ON;` on every connection
- Use explicit transactions for page/batch inserts
- Targeted indexes on `(project_id, updated_at)` for primary resources
---
## Schema Summary
| Table | Checkpoint | Purpose |
|-------|------------|---------|
| projects | 0 | Configured GitLab projects |
| sync_runs | 0 | Audit trail of sync operations |
| sync_cursors | 0 | Resumable sync state per primary resource |
| raw_payloads | 0 | Decoupled raw JSON storage |
| issues | 1 | Normalized issues |
| labels | 1 | Label definitions (unique by project + name) |
| issue_labels | 1 | Issue-label junction |
| merge_requests | 2 | Normalized MRs |
| notes | 2 | Issue and MR comments (with parent FKs) |
| mr_files | 2 | MR file changes (with rename tracking) |
| mr_labels | 2 | MR-label junction |
| documents | 3 | Unified searchable documents |
| document_labels | 3 | Document-label junction for fast filtering |
| embeddings | 3 | Vector embeddings (sqlite-vss, rowid=document_id) |
| embedding_metadata | 3 | Embedding provenance + change detection |
| documents_fts | 4 | Full-text search index (fts5) |
---
## Resolved Decisions
| Question | Decision | Rationale |
|----------|----------|-----------|
| Commit/file linkage | **Include MR→file links** | Enables "what MRs touched this file?" without full commit history |
| Labels | **Index as filters** | Labels are well-used; `document_labels` table enables fast `--label=X` filtering |
| Labels uniqueness | **By (project_id, name)** | GitLab API returns labels as strings; gitlab_id isn't always available |
| Sync method | **Polling for MVP** | Decide on webhooks after using the system |
| Notes sync | **Dependent resource** | Notes API is per-parent, not global; refetch on parent update |
| Hybrid ranking | **RRF over weighted sums** | Simpler, no score normalization needed |
| Embedding rowid | **rowid = documents.id** | Eliminates fragile rowid mapping during upserts |
| file-history CLI | **Post-MVP (CP6)** | Sharpens MVP checkpoint focus |
---
## Next Steps
1. User approves this spec
2. Generate Checkpoint 0 PRD for project setup
3. Implement Checkpoint 0
4. Human validates → proceed to Checkpoint 1
5. Repeat for each checkpoint