zeekay 6e02ab9e1a oss: NOTICE crediting Qdrant, on the branch that actually carries the code
hanzoai/vector is a Qdrant fork — 375 files on `master` name qdrant, the
history starts at Qdrant's own `init` commit, and Cargo.toml declares
Apache-2.0. The code was fully rebranded to `hanzo-vector` with no NOTICE,
so nothing in the distributed artifact named the upstream author.

The NOTICE text is not new. z wrote it on 2026-06-21 in 10dd93dfe
("chore: restore upstream attribution + NOTICE (OSS compliance)"), but that
commit landed on ci/canonical-docker-build-1776997064 and was never merged,
so `master` — the branch that carries the code — never got it. This carries
his wording over verbatim.

What is deliberately NOT carried over: 10dd93dfe also prepended two
copyright lines to LICENSE. Upstream Qdrant's LICENSE is the bare
Apache-2.0 text with no copyright line in it (the appendix still reads
"Copyright [yyyy] [name of copyright owner]"), so there is no upstream
notice there to retain — those lines would be an edit to an upstream
licence, not a preservation of one. Attribution belongs in NOTICE, which
is also what Apache-2.0 s4(d) asks for. LICENSE is untouched.

Note for whoever owns the default branch: `main` is a four-file stub
(README, LLM.md, CLAUDE.md, LICENSE) whose LICENSE reads "MIT License,
Copyright (c) 2026 Hanzo AI". No Apache-licensed code sits under it, so it
is not a redistribution violation today, but the default branch of a Qdrant
fork asserting MIT is misleading and should be reconciled with master.
2026-08-03 19:59:33 -07:00
2026-02-19 13:35:11 +01:00
2026-02-19 13:35:11 +01:00
2026-04-09 18:40:58 -07:00
2025-04-20 23:54:40 +02:00
2026-04-17 16:58:49 -07:00
2026-03-03 08:06:37 -08:00
…
2026-03-11 10:30:02 -07:00
2026-03-03 08:06:37 -08:00
2025-12-18 17:28:50 +01:00

Hanzo Vector

High-performance vector search engine for the Hanzo AI platform. Based on Qdrant.

Quick Start

docker run -p 6333:6333 -p 6334:6334 ghcr.io/hanzoai/vector:latest
  • REST API on port 6333
  • gRPC API on port 6334

Features

  • Dense and sparse vector search with filtering and payloads
  • Hybrid search combining semantic and keyword matching
  • Vector quantization (scalar, product, binary) for memory efficiency
  • Distributed deployment with sharding and replication
  • HNSW indexing with SIMD acceleration
  • Write-ahead logging and snapshot-based persistence
  • GPU acceleration (NVIDIA and AMD)

Configuration

Mount a custom config file:

docker run -p 6333:6333 \
  -v $(pwd)/config.yaml:/qdrant/config/production.yaml \
  -v $(pwd)/data:/qdrant/storage \
  ghcr.io/hanzoai/vector:latest

See config/config.yaml for all available options.

Building from Source

cargo build --release --bin qdrant

API

  • REST: OpenAPI 3.0 schema in openapi/
  • gRPC: Protocol definitions in lib/api/src/grpc/proto/

License

Apache License, Version 2.0. See LICENSE.


Based on Qdrant -- vector similarity search engine.

S
Description
High-performance vector database for AI embeddings
Readme Apache-2.0
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