AI Knowledge Base (public portfolio)

This repository is the public, stranger-runnable portfolio surface for the local hybrid RAG + MCP knowledge base.

• Private archive / personal corpus: stays in a separate private repo (ai_knowledge_base). Do not expect personal YouTube downloads or tip transcripts here.

• Public demo corpus: committed synthetic fixtures/ only. Tip-transcript docs from the private archive are absent on this sibling (curated out).

• Optional advanced path: copy channels.local.example.json → channels.local.json, add your own channels, sync with a short backfill (BACKFILL_DAYS = 7), then ingest — not the default smoke path. No auto-sync on clone.

• MCP: read-only public tool allowlist (search, discover, get_status, …). Mutation tools require an explicit private profile env flag and are not the default story here.

AI Knowledge Base

A local-first, vector-powered knowledge base for AI domain research. Ingests YouTube transcripts (optional local path) and committed fixtures (public smoke), with hybrid retrieval + optional cross-encoder rerank.

Binding architecture (KB1–KB5): docs/ARCHITECTURE.md
Public packaging intent: docs/PORTFOLIO_VISION.md
Personal vision (non-binding stack): docs/2026-01-30_vision.md
January architecture: docs/2026-01-30_architecture.md — historical / NON-BINDING (clean rewrite rejected).

Guide 01 (shared retrieval spine) is implemented. Guide 02 packaging DoD (LICENSE, empty channels + ignored overlay, path hygiene) is implemented. Guide 03: this public sibling is the portfolio public surface; private archive remains private. Optional private tip scrub is separate hygiene — not a blocker for having a public AI KB.

Features

• Vector search: Semantic search via local Ollama embeddings (nomic-embed-text @ 768 — not Gemma)

• Hybrid search: Vector + FTS → RRF fusion → optional pluggable CE (KB5)

• Fixture-first smoke: Committed synthetic fixtures; no personal corpus required

• Optional BYO sync: Local YouTube channel sync via ignored overlay (not required for demo)

• Discovery: Honest browse / digest / concepts / channel grouping (not a clustering product)

• 100% local: Ollama + LanceDB on your machine

Related MCP server: GraphRAG Llama Index MCP Server

Quick Start

# Install dependencies
uv sync

# Pull embedding model (nomic — not gemma, not mxbai)
ollama pull nomic-embed-text

# Fixture-first smoke (no personal corpus, no YouTube required)
uv run python -m src.ingest --fixtures
uv run python -m src.search "reciprocal rank fusion RRF" --hybrid --db data/lancedb
uv run python -m src.eval

Fixture smoke is the portfolio demo path. Live YouTube sync is optional (below) and not required for a green stranger clone.

Cross-encoder: local cross-encoder/ms-marco-MiniLM-L-6-v2 via sentence-transformers (pluggable). On the committed fixture golden set there is no claimed hit@K lift — keep the CE seam + degrade path for demos; do not read this as “CE improves relevance.” See docs/2026-07-12_ce_keep_note.md.

Optional: BYO YouTube live path

Not required for portfolio demo. No auto-sync on clone. Do not commit channels.local.json or downloaded transcripts.

# 1. Copy example → ignored local overlay
cp channels.local.example.json channels.local.json

# 2. Edit handles to your own channels (placeholders only in the example)

# 3. Default BACKFILL_DAYS is 7 (public demo window). Raise in src/config.py locally for deeper backfill.

# 4. Sync (network + yt-dlp)
uv run python -m src.youtube_sync

# 5. Ingest live downloads (path = config.TRANSCRIPTS_DIR)
uv run python -m src.ingest data/raw/youtube_transcripts/

# 6. Search smoke
uv run python -m src.search "your query" --hybrid --db data/lancedb

Architecture

ai-knowledge-base-public/
├── fixtures/                 # Public synthetic corpus + provenance + golden eval
├── data/                     # Local/ignored raw + LanceDB (not committed)
├── src/
│   ├── config.py             # Settings (nomic embeddings; N/K/CE; BACKFILL_DAYS=7)
│   ├── embed.py              # Ollama embeddings (nomic-embed-text)
│   ├── identity.py           # source_id / content_hash / embedding_version
│   ├── ingest.py             # Chunk + fixture/YouTube ingest + FTS
│   ├── search.py             # Shared retrieval spine (CLI)
│   ├── rerank.py             # Pluggable local CE adapter
│   ├── mcp_server.py         # RO public MCP (mutations behind private flag)
│   ├── discover.py           # Browse / digest / concepts / channel groups
│   ├── youtube_sync.py       # Optional BYO YouTube sync
│   └── eval/                 # Fixture golden eval stub
└── docs/
    └── ARCHITECTURE.md       # Binding KB1–KB5

Stack

Usage

Search

# Semantic search
uv run python -m src.search "best practices for MCP servers"

# Hybrid search (keyword + semantic → fusion → optional CE)
uv run python -m src.search "Claude Code hooks" --hybrid

# Disable CE for this call
uv run python -m src.search "RAG techniques" --hybrid --no-ce

# Show more results
uv run python -m src.search "RAG techniques" --limit 20

Discovery

# Channel grouping (honest label — not embedding clustering)
uv run python -m src.discover clusters

# What's new this week
uv run python -m src.discover digest --since 7d

# Random exploration
uv run python -m src.discover random

# Top concepts mentioned (heuristic term counts)
uv run python -m src.discover concepts

YouTube Sync (optional / local)

# Sync configured channels (new videos only) — uses ignored channels.local.json
uv run python -m src.youtube_sync

# Force re-check all channels
uv run python -m src.youtube_sync --force

Personal channel mutation via MCP is off on the public profile. Persist channels by editing ignored channels.local.json (not committed src/config.py).

Public default vs private overlay

# Optional: copy example → ignored overlay, then edit handles
cp channels.local.example.json channels.local.json
# never commit channels.local.json

get_status reports tracked_channels: 0 without an overlay. Launchd plist (scripts/com.aikb.youtube-sync.plist) is a template — replace REPLACE_WITH_REPO_ROOT with your clone path before launchctl load; macOS-only; not required for fixture smoke.

MCP Server (AI Agent Integration)

The knowledge base exposes an MCP server for AI coding assistants.

Setup

Add to your .cursor/mcp.json or Claude Code settings (replace cwd with your clone path — do not commit owner-specific absolute paths for public packaging):

{
  "mcpServers": {
    "ai-knowledge-base": {
      "command": "uv",
      "args": ["run", "python", "-m", "src.mcp_server"],
      "cwd": "/path/to/ai-knowledge-base-public"
    }
  }
}

Available Tools (public / default profile — read-only)

Mutation tools (add_channel, sync_now) are not on the public profile. Enable only with AI_KB_MCP_PRIVATE=1 (private local profile). Public results cite source_id / source_url, never owner filepaths.

Requirements

• Ollama must be running for embeddings (nomic-embed-text). On macOS, Ollama runs as a menu bar app with minimal idle resources (~50MB RAM).

Configuration

Edit src/config.py for embedding model (keep nomic-embed-text unless you accept full rebuild + eval), chunk sizes, RETRIEVAL_N / RETRIEVAL_K / CE_ENABLED, and BACKFILL_DAYS (public default 7; raise locally for deeper BYO backfill). Personal channel list lives in ignored channels.local.json (see example file).

License

MIT — see root LICENSE. Packaging DoD closed. This public sibling is the portfolio public surface; private archive remains private. Optional private tip scrub is separate hygiene, not required to have a public AI KB.