vector-rag-tool 0.1.0

RAG tool with local FAISS and remote S3 Vectors backends, using Ollama embeddings

vector-rag-tool

A CLI that provides local RAG with Ollama embeddings and FAISS vector search.

Features

• Semantic search using vector embeddings
• Multiple file types: Python, Markdown, YAML, JSON
• Document support: PDF, Word, Excel, PowerPoint via markitdown
• Fast local search with FAISS (~100ms queries)
• Optional S3 Vectors backend for cloud scale
• Incremental indexing with file hash tracking
• Configurable chunk size and overlap

Installation

Prerequisites:

• Python 3.13+
• Ollama with an embedding model

# Install Ollama and pull embedding model
brew install ollama
ollama pull embeddinggemma

# Install vector-rag-tool
git clone https://github.com/dnvriend/vector-rag-tool.git
cd vector-rag-tool
uv tool install .

Usage

# Preview what would be indexed (dry-run is default)
vector-rag-tool index "**/*.py" --store my-project

# Index files
vector-rag-tool index "**/*.py" --store my-project --no-dry-run

# Index multiple file types
vector-rag-tool index "**/*.py" "**/*.md" --store my-project --no-dry-run

# Query for relevant code
vector-rag-tool query "how does authentication work" --store my-project

# Get full chunk content for RAG grounding
vector-rag-tool query "database connection" --store my-project --full

# JSON output for piping
vector-rag-tool query "logging" --store my-project --json

# Force reindex all files
vector-rag-tool index "**/*.py" --store my-project --force --no-dry-run

# Index documents (PDF, Word, Excel)
vector-rag-tool index "docs/**/*.pdf" --store my-docs --no-dry-run

# Use S3 Vectors backend
vector-rag-tool index "**/*.py" --store my-store \
    --bucket my-vectors-bucket --profile aws-profile --no-dry-run

Store Management

vector-rag-tool store list              # List all stores
vector-rag-tool store create my-store   # Create empty store
vector-rag-tool store delete my-store --force  # Delete store

Options

Index Command

Option	Description
--store	Store name (required)
--chunk-size	Characters per chunk (default: 1500)
--chunk-overlap	Overlap between chunks (default: 200)
--force	Reindex all files, ignore cache
--no-dry-run	Actually index files
--bucket	S3 bucket for S3 Vectors backend
--profile	AWS profile for S3 backend

Query Command

Option	Description
--store	Store name (required)
--top-k	Number of results (default: 5)
--full	Return full chunk content
--snippet-length	Characters per snippet (default: 300)
--json	JSON output
--stdin	Read query from stdin

Global Options

Option	Description
-v	INFO level logging
-vv	DEBUG level logging
-vvv	TRACE level (library internals)

Development

make install        # Install dependencies
make test           # Run tests
make lint           # Run linting
make typecheck      # Type checking
make check          # All checks
make pipeline       # Full pipeline

License

MIT

Author

Dennis Vriend