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Kohaku Hub - Self-hosted HuggingFace alternative


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⚠️ Work In Progress - Not Production Ready

Self-hosted HuggingFace alternative with Git-like versioning for AI models and datasets. Fully compatible with the official huggingface_hub Python client.

Web UI Dark Mode

Join our community: https://discord.gg/xWYrkyvJ2s

Features

  • HuggingFace Compatible - Drop-in replacement for huggingface_hub, hfutils, transformers, diffusers
  • Native Git Clone - Standard Git operations (clone, pull, push) with Git LFS support
  • Git-Like Versioning - Branches, commits, tags via LakeFS
  • S3 Storage - Works with MinIO, AWS S3, Cloudflare R2, etc.
  • Large File Support - Git LFS protocol with automatic LFS pointers (>1MB files)
  • Organizations - Multi-user namespaces with role-based access
  • Web UI - Vue 3 interface with file browser, editor, commit history, Mermaid chart support
  • CLI Tool - Full-featured command-line interface
  • File Deduplication - Content-addressed storage by SHA256
  • Pure Python Git Server - No native dependencies, memory-efficient

Quick Start

Deploy with Docker

git clone https://github.com/KohakuBlueleaf/KohakuHub.git
cd KohakuHub

# Option 1: Use interactive generator (recommended)
python scripts/generate_docker_compose.py

# Option 2: Manual configuration
# cp docker-compose.example.yml docker-compose.yml
# Edit docker-compose.yml to change credentials and secrets

# Build frontend and start services
npm install --prefix ./src/kohaku-hub-ui
npm run build --prefix ./src/kohaku-hub-ui
docker-compose up -d --build

Access:

LakeFS credentials: Auto-generated in docker/hub-meta/hub-api/credentials.env

Use with Python

import os
from huggingface_hub import HfApi

os.environ["HF_ENDPOINT"] = "http://localhost:28080"
os.environ["HF_TOKEN"] = "your_token_here"

api = HfApi(endpoint=os.environ["HF_ENDPOINT"], token=os.environ["HF_TOKEN"])

# Create repo
api.create_repo("my-org/my-model", repo_type="model")

# Upload file
api.upload_file(
    path_or_fileobj="model.safetensors",
    path_in_repo="model.safetensors",
    repo_id="my-org/my-model",
)

# Download file
api.hf_hub_download(repo_id="my-org/my-model", filename="model.safetensors")

Use with Transformers/Diffusers

import os
os.environ["HF_ENDPOINT"] = "http://localhost:28080"
os.environ["HF_TOKEN"] = "your_token_here"

from diffusers import AutoencoderKL
vae = AutoencoderKL.from_pretrained("my-org/my-model")

CLI Tool

# Install
pip install -e .

# Interactive mode
kohub-cli

# Command mode
kohub-cli auth login
kohub-cli repo create my-org/my-model --type model
kohub-cli repo list --type model
kohub-cli org create my-org
kohub-cli org member add my-org alice --role admin

See docs/CLI.md for complete CLI documentation.

Git Clone (Native Git Support)

# Clone repository (fast - only metadata and small files)
git clone http://localhost:28080/namespace/repo-name.git

# For private repositories, use token authentication
git clone http://username:your-token@localhost:28080/namespace/private-repo.git

# Install Git LFS for large files
cd repo-name
git lfs install
git lfs pull  # Download large files (>1MB)

# All standard Git operations work
git pull
git checkout -b feature-branch
# (push operations coming soon)

How it works:

  • Files <1MB: Included directly in Git pack (fast clone)
  • Files >=1MB: Stored as LFS pointers (download via git lfs pull)
  • Pure Python implementation (no pygit2/libgit2 dependencies)
  • Automatic .gitattributes and .lfsconfig generation
  • Memory-efficient (handles repos of any size)

See docs/Git.md for complete Git clone documentation and implementation details.

Architecture

Stack:

  • FastAPI - HuggingFace-compatible API
  • LakeFS - Git-like versioning (branches, commits, diffs) via REST API
  • MinIO/S3 - Object storage with deduplication
  • PostgreSQL/SQLite - Metadata database (synchronous with db.atomic() transactions)
  • Vue 3 - Modern web interface

Implementation Notes:

  • LakeFS: Uses REST API directly (not the deprecated lakefs-client Python library), providing pure async operations without thread pool overhead
  • Database: Synchronous operations with Peewee ORM and db.atomic() for transaction safety. Supports multi-worker deployment (4-8 workers) for horizontal scaling. Future migration to peewee-async planned.

Data Flow:

  1. Small files (<10MB) → Base64 in commit payload
  2. Large files (>10MB) → Direct S3 upload via presigned URL (LFS protocol)
  3. All files linked to LakeFS commits for version control
  4. Downloads → 302 redirect to S3 presigned URL (no proxy)

See docs/API.md for detailed API documentation.

Configuration

Environment Variables (in docker-compose.yml):

# Application
KOHAKU_HUB_BASE_URL=http://localhost:28080
KOHAKU_HUB_LFS_THRESHOLD_BYTES=10000000  # 10MB

# S3 Storage
KOHAKU_HUB_S3_PUBLIC_ENDPOINT=http://localhost:29001
KOHAKU_HUB_S3_BUCKET=hub-storage

# Database
KOHAKU_HUB_DB_BACKEND=postgres
KOHAKU_HUB_DATABASE_URL=postgresql://hub:pass@postgres:5432/hubdb

# Auth
KOHAKU_HUB_SESSION_SECRET=change-me-in-production
KOHAKU_HUB_REQUIRE_EMAIL_VERIFICATION=false

See config-example.toml for all options.

Development

Backend:

pip install -e .

# Single worker (development)
uvicorn kohakuhub.main:app --reload --port 48888

# Multi-worker (production-like testing)
uvicorn kohakuhub.main:app --host 0.0.0.0 --port 48888 --workers 4

# Note: Database uses db.atomic() for transaction safety in multi-worker setups
# Note: In production, access via nginx on port 28080

Frontend:

npm install --prefix ./src/kohaku-hub-ui
npm run dev --prefix ./src/kohaku-hub-ui

Testing:

python scripts/test.py
python scripts/test_auth.py

Documentation

Security Notes

⚠️ Before Production:

  • Change all default passwords in docker-compose.yml
  • Set secure KOHAKU_HUB_SESSION_SECRET
  • Set secure LAKEFS_AUTH_ENCRYPT_SECRET_KEY
  • Use HTTPS with reverse proxy
  • Only expose port 28080 (Web UI)

Known Limitations

  • Repository transfer between namespaces not fully supported
  • Some HuggingFace API endpoints may be incomplete
  • No rate limiting yet
  • See docs/TODO.md for full list

License

AGPL-3.0 (may change to more permissive license later)

Support

Acknowledgments

  • HuggingFace - API design and client library
  • LakeFS - Data versioning engine (REST API)
  • MinIO - Object storage

Note: Active development. APIs may change. Not for production use yet.

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