Weave CLI

A fast, AI-powered command-line (CLI) tool for managing your vector database (VDBs).

Built in Go for performance and ease of use (single binary).

Quick Start

Installation

git clone https://github.com/maximilien/weave-cli.git
cd weave-cli
./build.sh
# Binary available at bin/weave

Choose Your Vector Database

Weave CLI supports 10 vector databases. Choose the one that best fits your needs:

VDB	Status	Local	Cloud	Best For
Weaviate	✅ Stable	✅	✅	Production, all features, easiest setup
Qdrant	✅ Stable	✅	✅	Rust performance, HNSW index, filtering
Milvus	✅ Stable	✅	✅	High performance, horizontal scaling
Chroma	✅ Stable	✅	✅	macOS only, simple setup, embeddings
Supabase	✅ Stable	✅	✅	PostgreSQL + pgvector, cost-effective
Neo4j	✅ Stable	✅	⚠️ Untested	Graph + vector search, Cypher queries
MongoDB	✅ Stable	❌	✅	Atlas Vector Search, existing MongoDB users
Pinecone	🟢 Beta	❌	✅	Serverless, auto-scaling, managed only
OpenSearch	✅ Stable	✅	✅	AWS OpenSearch, k-NN + BM25 hybrid
Elasticsearch	🟢 Beta	✅	✅	Elastic Cloud, HNSW vector + BM25 hybrid

📖 See Vector Database Support Matrix for detailed feature comparison

Quick Setup (Weaviate - Recommended)

# Interactive configuration - fastest way to get started
weave config create --env

# Follow prompts to enter:
# - WEAVIATE_URL
# - WEAVIATE_API_KEY
# - OPENAI_API_KEY

# Verify setup
weave health check

For other databases, see their setup guides linked in the table above.

Basic Usage

# List collections (all configured VDBs)
weave cols ls

# List collections from specific database types
weave cols ls --weaviate            # Weaviate only
weave cols ls --qdrant-local        # Qdrant local only
weave cols ls --qdrant-cloud        # Qdrant cloud only
weave cols ls --milvus-local        # Milvus local only
weave cols ls --milvus-cloud        # Milvus cloud (Zilliz) only
weave cols ls --chroma-local        # Chroma local only
weave cols ls --chroma-cloud        # Chroma cloud only
weave cols ls --supabase            # Supabase only
weave cols ls --neo4j-local         # Neo4j local only
weave cols ls --neo4j-cloud         # Neo4j cloud (Aura) only
weave cols ls --mongodb             # MongoDB Atlas only
weave cols ls --pinecone            # Pinecone only
weave cols ls --opensearch-local    # OpenSearch local only
weave cols ls --opensearch-cloud    # OpenSearch cloud (AWS) only
weave cols ls --elasticsearch-local # Elasticsearch local only
weave cols ls --elasticsearch-cloud # Elasticsearch cloud (Elastic) only
weave cols ls --mock                # Mock database only
weave cols ls --all                 # All configured databases

# Create a collection
weave cols create MyCollection --text

# Add documents
weave docs create MyCollection document.txt
weave docs create MyCollection document.pdf

# Search with natural language
weave cols q MyCollection "search query"

# AI-powered Read, Evaluate, Print, Loop (REPL) mode or agent mode
weave
> show me all my collections
> create TestDocs collection
> add README.md to TestDocs

# Or doing one query at a time
weave query "show me all my collections"

# List available embeddings
weave embeddings list
weave emb ls --verbose

# Create collection with specific embedding (used as default for all documents)
weave cols create MyCollection --embedding text-embedding-3-small
weave cols create MyCollection -e text-embedding-ada-002

# Get AI-powered schema suggestions for your documents
weave schema suggest ./docs --collection MyDocs --output schema.yaml

# Get AI-powered chunking recommendations
weave chunking suggest ./docs --collection MyDocs --output chunking.yaml

Key Features

• 🤖 AI-Powered - AI Agent mode, natural language interface with GPT-4o multi-agent system, schema suggestions, and chunking recommendations
• ⚡ Fast & Easy - Written in Go with simple CLI and interactive REPL (AI Agent mode) with real-time progress feedback
• 🌐 Flexible - Weaviate Cloud, local instances, or built-in mock database
• 🔌 Extensible - Vector database abstraction layer supporting multiple backends (Weaviate, Milvus, Supabase PGVector, MongoDB Atlas, Chroma, Qdrant, Neo4j, OpenSearch)
• 📦 Batch Processing - Parallel processing of entire directories
• 📄 PDF Support - Intelligent text extraction and image processing
• 🔍 Semantic Search - Vector-based similarity search with natural language
• 🧠 AI Schema & Chunking - Analyze documents and get AI-powered schema and optimal chunk size recommendations
• 📊 Embeddings - List and explore available embedding models
• ⏱️ Configurable Timeouts - Default 10s timeout, adjustable per command

Documentation

Core Documentation

• 📖 User Guide - Complete feature documentation
• 📋 Changelog - Version history and updates
• 🗂️ VDB Support Matrix - Database feature comparison

Guides

• 🤖 AI Agents - REPL mode with natural language query system
• 🔌 MCP AI Tools API - Using AI tools via MCP server
• 📦 Batch Processing - Directory processing guide
• 📚 Vector DB Abstraction - Multi-database support architecture
• 🎬 Demos - Video demos and tutorials

Database-Specific

• Chroma Documentation - Chroma integration guide (Stable)
• Milvus Documentation - Milvus integration guide (Beta)
• MongoDB Atlas Documentation - MongoDB Atlas setup guide (Stable)
• Neo4j Documentation - Neo4j integration guide (Experimental)
• OpenSearch Documentation - OpenSearch integration guide (Experimental)
• Pinecone Documentation - Pinecone integration guide (Beta)
• Qdrant Documentation - Qdrant integration guide (Stable)
• Supabase Documentation - Supabase integration guide (Alpha)
• Weaviate Documentation - Weaviate integration status (Stable)

Advanced Usage

Configuration Options

Auto-Configuration

Weave CLI automatically detects missing configuration:

# Try any command - you'll get prompted to configure interactively
weave cols ls

# Or install latest release of weave-mcp for REPL mode
weave config update --weave-mcp

Configuration Precedence (highest to lowest):

1. Command-line flags - weave query --model gpt-4
2. Environment variables - export OPENAI_MODEL=gpt-4
3. config.yaml (optional) - For advanced customization
4. Built-in defaults

Configuration Location (precedence order):

1. Local directory (.env, config.yaml) - Project-specific configuration
2. Global directory (~/.weave-cli/.env, ~/.weave-cli/config.yaml) - User-wide configuration

# Create configuration in global directory
weave config create --env --global

# Sync local configuration to global directory
weave config sync

# View which configuration location is being used
weave config show

See the User Guide for detailed configuration options.

Vector Database Selection

Control which vector database(s) to operate on with these flags:

Important: Database selection behavior depends on your configuration:

• Single Database: If only one DB is configured, it's used automatically (no flags needed!)
• Multiple Databases:
  • Read operations (ls, show, count) use all databases by default
  • Write/delete operations use smart selection:
    1. Default Database: Uses VECTOR_DB_TYPE from .env or config
    2. Weaviate Collection Search: For --weaviate, searches all Weaviate databases for the collection
    3. Manual Selection: Use --vector-db-type (or --vdb) to specify explicitly

# Single database setup - no flags needed!
weave docs create MyCollection doc.txt       # Uses your only configured DB

# Multiple databases with VECTOR_DB_TYPE set
export VECTOR_DB_TYPE=weaviate-cloud
weave docs create MyCollection doc.txt       # Uses weaviate-cloud (default)
weave docs delete MyCollection doc123        # Uses weaviate-cloud (default)

# Override default with --vdb (short) or --vector-db-type (long)
weave docs create MyCollection doc.txt --vdb weaviate-local
weave docs create MyCollection doc.txt --vector-db-type supabase

# --weaviate tries both weaviate-cloud and weaviate-local
weave docs ls MyCollection --weaviate        # Searches both for collection
weave cols delete MyCollection --weaviate    # Searches both for collection

# Read operations work with specific or all databases
weave cols ls --weaviate                     # All Weaviate databases
weave cols ls --supabase                     # Supabase only
weave cols ls --all                          # All configured databases (default)

# Query multiple databases at once
weave cols query MyCollection "search" --weaviate --supabase

Database Selection Priority for Single-DB Operations:

1. If only one database configured → use it
2. If VECTOR_DB_TYPE set → use as default
3. If --weaviate flag used → try all Weaviate databases for the collection
4. Otherwise → show error with available options

Summary Views and Filtering (New in v0.7.2)

View database status and collections across multiple databases with summary tables and progressive output:

# Collections summary across all databases (default for multiple VDBs)
weave cols ls                    # Shows summary table by default
weave cols ls -S                 # Explicit summary flag (shorthand)
weave cols ls --summary          # Explicit summary flag (long form)

# Health check with progressive output (new in v0.7.2)
weave health check               # Shows summary table, results appear
weave health check -S            # Same as above (shorthand)

# Filter databases by deployment type (new in v0.7.2)
weave config list --cloud        # Show only cloud databases
weave config list --local        # Show only local databases

weave health check --cloud       # Check only cloud databases
weave health check --local       # Check only local databases
weave health check --local -S    # Local databases summary

# Force detailed view for single database
weave cols ls --weaviate         # Detailed list (default for single VDB)
weave health check weaviate      # Detailed health check

# Collections summary also supports filtering
weave cols ls --cloud            # Collections from cloud databases only
weave cols ls --local -S         # Local collections summary

Summary Table Features:

• Progressive Output: Results appear immediately as they're retrieved/checked (no waiting!)
• Status Indicators: ✓ OK (green) or ✗ FAIL (red) with color coding
• Footer Statistics: Total count, collections/healthy count, failures
• Auto-Selection: Summary for multiple VDBs, detailed for single VDB
• Cloud/Local Filtering: Filter by deployment type with --cloud or --local flags
• Consistent UX: Same behavior across cols ls, health check, and config list

More Examples

# Batch process documents with parallel workers
weave docs batch --directory ./docs --collection MyCollection --parallel 3

# Convert CMYK PDFs to RGB
weave docs pdf-convert document.pdf --rgb

# Text-only PDF extraction (faster, no images)
weave docs create MyCollection document.pdf --skip-all-images

# Natural language queries with AI agents
weave q "find all empty collections"
weave query "create TestDocs and add README.md" --dry-run

# Configure timeout for slow connections
weave cols ls --timeout 30s
weave health check --timeout 60s

# Create collections and documents with specific embeddings
weave cols create MyCollection --embedding text-embedding-3-small
weave docs create MyCollection document.txt --embedding text-embedding-3-small
weave docs create MyCollection report.pdf --embedding text-embedding-ada-002

Database Support

Weave CLI features a pluggable vector database abstraction layer that allows seamless switching between different vector database backends.

Support Matrix

Database	Type	Status	Maturity	Docs
Weaviate Cloud	weaviate-cloud	✅ Production Ready	Stable	Guide
Weaviate Local	weaviate-local	✅ Production Ready	Stable	Guide
Milvus Local	milvus-local	✅ Functional	Beta - Feature complete, local testing ready	Guide
Milvus Cloud	milvus-cloud	✅ Functional	Beta - Zilliz cloud integration ready	Guide
Supabase	supabase	✅ Functional	Alpha - Feature complete, needs testing	Guide
MongoDB Atlas	mongodb	✅ Functional	Experimental - Vector search requires index setup	Guide
Chroma Local	chroma-local	✅ Production Ready	Stable - Full CRUD, tested with v2 API ⚠️ macOS only	Guide
Chroma Cloud	chroma-cloud	✅ Functional	Beta - Cloud integration ⚠️ macOS only	Guide
Qdrant Local	qdrant-local	✅ Production Ready	Stable - HNSW vector search, full CRUD	Guide
Neo4j Local	neo4j-local	✅ Functional	Experimental - Graph + vector search	Guide
OpenSearch Local	opensearch-local	✅ Functional	Experimental - k-NN with HNSW algorithm	Guide
OpenSearch Cloud	opensearch-cloud	✅ Functional	Experimental - AWS OpenSearch Service	Guide
Mock	mock	✅ Testing Only	Stable	-

Maturity Levels

• Stable: Production-ready, well-tested, recommended for all use cases
• Beta: Feature complete, functional, ready for testing and feedback
• Alpha: Feature complete, functional, recommended for development/testing
• Experimental: Basic functionality working, may require manual setup, use with caution

Platform Compatibility

⚠️ Important Platform Limitations:

• Chroma: macOS only (CGO dependency on libtokenizers)
  • Linux/Windows users: Use Weaviate, Milvus, Qdrant, or Supabase instead
  • CI/CD on Linux: Skip Chroma tests with --skip chroma
• MongoDB: Cloud (Atlas) only - no local/self-hosted support
  • Offline deployments: Use Weaviate, Milvus, Qdrant, or Neo4j instead
• All other VDBs: Cross-platform (Linux, macOS, Windows)

Additional Resources

• Vector DB Integrations Planning - Roadmap for upcoming database support
• Vector DB Abstraction Guide - Architecture details and how to add new databases

Abstraction Benefits

• Unified Interface - Same commands work across all database types
• Easy Migration - Switch databases without changing workflows
• Extensible - Add new vector databases with minimal code changes
• Type Safety - Compile-time validation of database operations
• Error Handling - Structured error types with context and recovery

See 📚 Vector DB Abstraction Guide for implementation details and adding new database support.

Development

# Setup development environment (installs linters, PDF tools, etc.)
./setup.sh

# Build, test, and lint
./build.sh
./test.sh
./lint.sh

See User Guide for detailed development instructions.

Contributing

Contributions welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Make your changes with tests
4. Run ./test.sh and ./lint.sh
5. Submit a pull request

Links

Video Demos

• Full Demo (5 min) - Complete feature walkthrough
• Quick Demo (2 min) - Quick overview
• REPL Demo - AI-powered natural language interface

Interactive Demos

Run these scripts locally for hands-on demonstrations:

• Configuration Demo - Interactive setup and configuration management
• Supabase Demo - Supabase (PostgreSQL + pgvector) integration

See demos/README.md for details.

Resources

• GitHub Repository
• Documentation
• User Guide

Presentations

Recent presentations about Weave CLI:

• AI by the Bay (Nov 2025) - Vector database management with AI agents

  • Event: AI by the Bay Conference

• SV AI Demo 2 (Nov 2025) - Multi-database vector management demo

  • Event: SV AI Demo Meetup

License

MIT License - see LICENSE file for details.