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Command line interface to interact with weaviate

Project description

Weaviate CLI

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Build Status PyPI version

A powerful command-line interface for managing and interacting with Weaviate vector databases directly from your terminal.

Key Features

  • Collections: Create, update, delete and get collection configurations
  • Data Management: Import, query, update and delete data with various search types (vector, keyword, hybrid)
  • Multi-tenancy: Manage tenants and their states across collections
  • Backup & Restore: Create and restore backups with support for S3, GCS and filesystem
  • Sharding: Monitor and manage collection shards
  • Flexible Configuration: Configure vector indexes, replication, consistency levels and more

Quick Start

Install using pip:

pip install weaviate-cli

Basic Usage

# Show available commands
weaviate-cli --help

# Create a collection
weaviate-cli create collection --collection movies --vectorizer transformers

# Import test data
weaviate-cli create data --collection movies --limit 1000

# Query data
weaviate-cli query data --collection movies --search-type hybrid --query "action movies"

Core Commands

  • create: Create collections, tenants, backups or import data
  • delete: Remove collections, tenants or data
  • update: Modify collection settings, tenant states or data
  • get: Retrieve collection info, tenant details or shard status
  • query: Search data using various methods
  • restore: Restore backups from supported backends

Configuration

Weaviate CLI allows you to configure your cluster endpoints and parameters through a configuration file. By default, the CLI looks for a configuration file at ~/.config/weaviate/config.json. If this file does not exist, it will be created with the following default values:

{
    "host": "localhost",
    "http_port": "8080",
    "grpc_port": "50051"
}

You can also specify your own configuration file using the --config-file option:

weaviate-cli --config-file /path/to/your/config.json

The configuration file should be a JSON file with the following structure:

{
    "host": "your-weaviate-host",
    "http_port": "your-http-port",
    "grpc_port": "your-grpc-port",
    "auth": {
        "type": "api_key",
        "api_key": "your-api-key"
    }
}

If you are using a remote Weaviate instance, you can use the weaviate-cli command to authenticate with your Weaviate instance. Here you can see an example on how the configuration file should look like if you are connecting to a WCD cluster:

 {
     "host": "thisisaninventedcluster.url.s3.us-west3.prov.weaviate.cloud",
     "auth": {
         "type": "api_key",
         "api_key": "jfeRFsdfRfSasgsDoNOtTrYToUsErRQwqqdZfghasd"
     },
    "headers":{
        "X-OpenAI-Api-Key":"OPEN_AI_KEY",
        "X-Cohere-Api-Key":"Cohere_AI_KEY",
        "X-JinaAI-Api-Key":"JINA_AI_KEY"
        }
 }

Requirements

  • Python 3.9+
  • Weaviate instance (local or remote)

Documentation

Detailed documentation will be added soon.

Supported Model Provider

  • Contextionary
  • Transformers
  • OpenAI
  • Ollama
  • Cohere
  • JinaAI

Community & Support

Contributing

We welcome contributions! Please see our Contributing Guidelines for details.

License

BSD-3-Clause License

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