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CyborgDB can be deployed as a Python service using pip installation. This approach provides a lightweight alternative to Docker, allowing you to run the CyborgDB service directly in your Python environment with full control over dependencies and configuration.
Looking to use Docker? Check out our Docker Quickstart Guide.

Overview

The Python service is ideal for developers who prefer managing Python environments directly, need custom dependency management, or want to integrate CyborgDB service into existing Python applications. It provides the same REST API functionality as the Docker version.
1

Get an API Key

To use CyborgDB, you need an API key. You can get one from the CyborgDB Admin Dashboard.For quick evaluation, you can generate a temporary demo key using any of the SDKs:
import cyborgdb
print(cyborgdb.get_demo_api_key())
Then use the printed key as your CYBORGDB_API_KEY when starting the service, and as the api_key when connecting with an SDK client.Make sure to keep your API key secure and do not share it publicly.
2

Check Prerequisites

Ensure you have the required Python version and environment tools:
  • Python: 3.10, 3.11, 3.12, 3.13, or 3.14
  • Package Manager: conda (recommended) or pip with virtual environment
While conda is mentioned in the build instructions, the wheel works with any Python environment manager including pip, pipenv, poetry, etc.
3

Choose Your Storage Backend (Optional)

The service ships with three storage backends. Skip this step and you get disk (embedded RocksDB) by default — the data directory is ~/.cyborgdb/data.
  • Disk (default) — embedded RocksDB on local disk. Persistent, no external dependencies. Best for single-node deployments and edge devices.
  • S3 — AWS S3 or any S3-compatible store (MinIO, Cloudflare R2, …). Best for cloud-native and multi-node deployments.
  • Memory — in-process only, nothing persists across restarts. For tests and ephemeral indexes.
For full details, see the Backing Stores guide.
v0.17 collapsed the storage surface. The previous standalone, postgres, and redis backends and the catch-all CYBORGDB_CONNECTION_STRING are gone — switch standalonedisk and use the new CYBORGDB_DISK_PATH / CYBORGDB_S3_* variables.
4

Install CyborgDB Service

Install the CyborgDB service package using conda and pip:
# Create conda environment
conda create -n cyborgdb-service python=3.12
conda activate cyborgdb-service

# Install the service
pip install cyborgdb-service

# If you want to use automatic embedding generation, install with:
pip install cyborgdb-service[embeddings]
Using conda or a virtual environment is strongly recommended to avoid dependency conflicts with other Python packages.
5

Configure Environment Variables

Set the required environment variables for your deployment:
# Minimal — disk is the default; data goes to ~/.cyborgdb/data
export CYBORGDB_API_KEY=cyborg_your_api_key_here
# Optional: pin the data directory
# export CYBORGDB_DISK_PATH=/var/lib/cyborgdb
Using a .env file is the most convenient method as it persists your configuration and keeps sensitive data out of your shell history.
For more information on environment variables, refer to this guide.
6

Start the Service

Run the CyborgDB service using the installed command:
cyborgdb-service
The service will start and display startup information including:
  • Configured storage backend (memory, disk, or s3)
  • Server URL (default: http://localhost:8000)
  • Available API endpoints
For additional configuration options, run cyborgdb-service --help to see all available command-line arguments.
7

Verify Installation

Once the service is running, verify it’s working correctly:Health Check:
curl http://localhost:8000/v1/health
API Documentation: Navigate to http://localhost:8000/v1/docs to explore the interactive API documentation.You should see a response indicating the service is healthy and ready to accept requests.
8

Advanced Configuration

For production deployments, consider these additional configurations:
VariableDescriptionRequiredExample
CYBORGDB_API_KEYYour CyborgDB API keycyborg_abc123...
CYBORGDB_DB_TYPEStorage backend (memory, disk, s3)❌ (defaults to disk)s3
CYBORGDB_DISK_PATHData directory for disk storage/var/lib/cyborgdb
CYBORGDB_S3_BUCKETBucket name for s3 storageRequired for S3my-bucket
CYBORGDB_S3_REGIONRegion for s3 storageus-east-1
PORTService port8000
SSL_CERT_PATHPath to SSL certificate file/etc/ssl/certs/server.crt
SSL_KEY_PATHPath to SSL private key file/etc/ssl/private/server.key
Without CYBORGDB_DB_TYPE, the service uses disk storage rooted at ~/.cyborgdb/data. For the full list (including S3 credentials and KMS), see the Environment Variables guide.
9

Next Steps

Now that your CyborgDB service is running, you can interact with it using client SDKs:Install Client SDKs:
pip install cyborgdb

REST API Reference

Learn how to use the REST API for direct integration

Python SDK Reference

Learn how to use the Python SDK for direct integration

JS/TS SDK Reference

Learn how to use the JavaScript/TypeScript SDK for direct integration

Go SDK Reference

Learn how to use the Go SDK for direct integration
AspectPython ServiceDocker Service
Installationpip installdocker run
DependenciesManaged by pip/condaBundled in container
Resource UsageLower overheadHigher overhead
Environment IsolationPython virtualenvContainer isolation
Deployment ComplexitySimple Python deploymentContainer orchestration
ConfigurationEnvironment variables/filesEnvironment variables
Best ForDevelopment, Python-heavy workflowsProduction, cloud deployment
Both approaches provide identical CyborgDB functionality. Choose based on your deployment preferences and infrastructure requirements.