GitHub Semantic Search

🦞 Super GitHub — AI-Native GitHub Assistant

> Powered by the same Embedder + Qdrant + LLM architecture as elite memory systems. > Index repos, search semantically, monitor proactively — all with natural language.

Architecture

Query → [LLM: understand intent] → [Embedder: vectorize] → [Qdrant: semantic search] → [gh CLI: act]

Three-layer system (same as production memory pipelines):

| Layer | Component | Role | |-------|-----------|------| | Embedder | Ollama nomic-embed-text | Converts text → 768-dim vectors | | Vector Store | Qdrant (local) | Stores & searches vectors by similarity | | Action Layer | gh CLI | Executes GitHub operations |

Prerequisites

Quick Start

# 1. Initialize Qdrant collection
python scripts/github_indexer.py init
2. Index a repo
python scripts/github_indexer.py add owner/repo --all
3. Search with natural language
python scripts/github_search.py "memory search failing in agent" --limit 10
4. Monitor for keywords
python scripts/github_monitor.py watch owner/repo --events issues,ci --keywords bug,broken,urgent

Scripts

| Script | Purpose | |--------|---------| | github_indexer.py | Index repos (issues, PRs, metadata) into Qdrant | | github_search.py | Natural language semantic search | | github_monitor.py | Proactive monitoring with keyword alerts |

Detailed Commands

Index (github_indexer.py)

python github_indexer.py init                    # Create Qdrant collection
python github_indexer.py add owner/repo --all     # Index everything
python github_indexer.py add owner/repo --issues # Issues only
python github_indexer.py add owner/repo --prs    # PRs only
python github_indexer.py add owner/repo --repo   # Repo metadata
python github_indexer.py status                   # Show indexed data
python github_indexer.py rm owner/repo           # Remove from index

Search (github_search.py)

python github_search.py "query"                            # Search all
python github_search.py "query" --repo owner/repo         # Filter by repo
python github_search.py "query" --type issue              # Filter by type
python github_search.py "query" --limit 20               # More results
python github_search.py "query" --repo owner/repo --ci    # Show CI runs

Monitor (github_monitor.py)

python github_monitor.py watch owner/repo                  # Start watching
python github_monitor.py watch owner/repo --events issues,ci
python github_monitor.py status                            # Show watches
python github_monitor.py check                            # Run checks
python github_monitor.py unwatch owner/repo               # Stop watching

Memory System Analogy

| Component | GitHub Skill | Memory System | |-----------|-------------|---------------| | Data | Issues, PRs, code | Conversations | | Embedder | nomic-embed-text | nomic-embed-text | | Vector Store | Qdrant | Qdrant | | Add | github_indexer.py | mem0 add | | Search | github_search.py | mem0 search |

Why Vector Search vs Keyword?

| Approach | "memory problems" query | |----------|--------------------------| | Keyword | Exact match only | | Vector (this) | "memory leak", "OOM", "out of memory" |

Setup Checklist

# 1. Initialize Qdrant collection
python scripts/github_indexer.py init
2. Index a repo
python scripts/github_indexer.py add owner/repo --all
3. Search with natural language
python scripts/github_search.py "memory search failing in agent" --limit 10
4. Monitor for keywords
python scripts/github_monitor.py watch owner/repo --events issues,ci --keywords bug,broken,urgent