Metadata-Version: 2.4
Name: cyborgdb
Version: 0.11.0
Summary: CyborgDB Python Client
Author: Cyborg Inc.
License: MIT
Project-URL: Homepage, https://www.cyborg.co
Project-URL: Documentation, https://docs.cyborg.co
Keywords: OpenAPI,OpenAPI-Generator,CyborgDB Service
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: C++
Classifier: Topic :: Database
Classifier: Topic :: Database :: Database Engines/Servers
Classifier: Topic :: Security :: Cryptography
Classifier: Topic :: Software Development :: Libraries
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: urllib3<3.0.0,>=1.25.3
Requires-Dist: python-dateutil>=2.8.2
Requires-Dist: pydantic>=2
Requires-Dist: typing-extensions>=4.7.1
Dynamic: license-file

# CyborgDB Python SDK

The **CyborgDB Python SDK** provides a comprehensive client library for interacting with [CyborgDB](https://www.cyborg.co), the first Confidential Vector Database. This SDK enables you to perform encrypted vector operations including ingestion, search, and retrieval while maintaining end-to-end encryption of your vector embeddings.

This SDK provides an interface to `cyborgdb-service` which you will need to separately install and run in order to use the SDK. For more info, please see our [docs](https://docs.cyborg.co)

**Why CyborgDB?**

Vector Search powers critical AI applications like RAG systems, recommendation engines, and semantic search. The CyborgDB JS/TS SDK brings confidential computing to your web applications and Node.js services, ensuring vector embeddings remain encrypted throughout their entire lifecycle while providing fast, accurate search capabilities.

**Key Features**

* **End-to-End Encryption**: All vector operations maintain encryption with client-side keys
* **Batch Operations**: Efficient batch queries and upserts for high-throughput applications
* **Flexible Indexing**: Support for multiple index types (IVFFlat, IVFPQ, etc.) with customizable parameters

**Installation**

1. Install `cyborgdb-service`

```bash
# Install the CyborgDB Service
pip install cyborgdb-service
```

2. Install `cyborgdb` SDK:

```bash
# Install the CyborgDB Python SDK
pip install cyborgdb
```

**Usage**

```py
# TBD
```

**Advanced Usage**

**Batch Queries**

```py
# TBD
```

**Metadata Filtering**

```py
# TBD
```

**Index Training**

```py
# TBD
```

**Documentation**

For more detailed documentation, visit:
* [CyborgDB Documentation](https://docs.cyborg.co/)

**License**

The CyborgDB Python SDK is licensed under the MIT License - see the [LICENSE](./LICENSE) file for details.

**About CyborgDB**

CyborgDB is dedicated to making AI safe and secure through confidential computing. We develop solutions that enable organizations to leverage AI while maintaining the confidentiality and privacy of their data.

[Visit our website](https://www.cyborg.co/) | [Contact Us](mailto:hello@cyborg.co)
