qdrant

v2026.09.24

Qdrant vector database: collections, points, payload filtering, indexing, quantization, snapshots, and Docker/Kubernetes deployment. Use when managing Qdrant collections, performing vector searches with payload filters, configuring HNSW indexes or quantization, or deploying Qdrant clusters. Keywords: Qdrant, vector database, HNSW, quantization, semantic search.

GitHub
安装命令
npx skhub add itechmeat/qdrant
Markdown
SKILL.md

Qdrant (Skill Router)

This file is intentionally introductory.

It acts as a router: based on your situation, open the right note under references/.

Release Highlights (1.19.0 → 1.19.1)

  • TurboQuant 4-bit as primary storage: the "turbo4" datatype stores only 4-bit quantized vectors, sparing disk space on originals.
  • Per-component memory strategy: collection components now take "memory": "cold" / "cached" / "pinned" for fine-grained control over memory vs performance. Deprecates max_resident_memory_percent of strict mode in favor of the new global quota API.
  • Keyword prefix match: {"match": {"prefix": "..."}} in filters matches keywords by prefix; must be enabled in the keyword index.
  • Sparse search: per-query IDF corpus for better per-tenant/sparse ranking.
  • Slice filtering: sliced scroll / deterministic sampling via a slice filter condition.
  • Global quota API: central place to cap cluster resource usage (supersedes the strict-mode memory ceiling).
  • Routing token: deterministic read routes when the read affinity option is in use.
  • 1.19.1: 4-bit TurboQuant SIMD rework and batched HNSW searches (faster scoring), quantized scoring prefetch, plus input hardening — rejects empty dense vectors, vectors larger than 65536, and ./.. in collection names (security).

Release Highlights (1.16.3 → 1.18.0)

  • Monitoring + ops: new APIs for optimization progress/stages and cluster-wide telemetry, plus a dedicated HTTP port option for /metrics.
  • Security: audit access logging and secondary API key support (rotation).
  • Retrieval: relevance feedback and Weighted RRF for hybrid ranking.
  • Write semantics: update_mode for upserts (upsert / update / insert).
  • 1.18.0: TurboQuant adds an aggressive vector-compression path, collections can add/delete named vectors in place, and operators get low-memory/strict-memory knobs plus deeper memory reporting.

Patch Notes (1.18.1 → 1.18.2)

  • 1.18.2 security: fixes a REST auth whitelist bypass on specially crafted paths and a heap-read vulnerability with malformed snapshots. Upgrade promptly if Qdrant is exposed with auth/whitelisting or accepts uploaded snapshots.
  • 1.18.2: logs slow operations during shard WAL recovery and clears the ID-tracker cache after building segments.
  • Filter behavior is corrected for indexed integer range filters that receive float values and for {match: {except: []}} on payload-indexed fields.
  • Empty vector requests no longer trigger a panic path; treat them as invalid input and validate caller-side before sending them to Qdrant.
  • TurboQuant heap-memory reporting is more accurate, so operators should trust current metrics over older baselines when checking compression impact.
  • Snapshot upload authorization is tightened; do not assume restore/upload endpoints are safe without the same auth review you apply to the main API surface.

Breaking / Upgrade Notes (1.17.0)

  • gRPC clients: response format for vector fields changed in gRPC. Upgrade official Qdrant client libraries and validate any custom gRPC integrations.
  • Storage upgrades: RocksDB is removed in favor of gridstore. If you are on v1.15.x, do not upgrade directly to v1.17.x — upgrade one minor version at a time.

Additional Upgrade Notes (1.18.0)

  • Internal gRPC endpoints now enforce API key/JWT authentication when auth is enabled; validate internal service-to-service traffic before upgrade if you previously relied on private-network-only trust.
  • Snapshot restore from URL can now be disabled by config, which is relevant for hardened/self-hosted environments.

Start here (fast)

  • New to Qdrant? Read: references/concepts.md.
  • Want the fastest local validation? Read: references/quickstart.md + references/deployment.md.
  • Integrating with Python? Read: references/api-clients.md.

Choose by situation

Data modeling

  • What should go into vectors vs payload vs your main DB? Read: references/modeling.md.
  • Working with IDs, upserts, and write semantics? Read: references/points.md.
  • Need to understand payload types and update modes? Read: references/payload.md.

Retrieval (search)

  • One consolidated entry point (search + filtering + explore + hybrid): references/retrieval.md.

Performance & indexing

  • Index types and tradeoffs: references/indexing.md.
  • Storage/optimizer internals that matter operationally: references/storage.md + references/optimizer.md.
  • Practical tuning, monitoring, troubleshooting: references/ops-checklist.md.

Deployment & ops

  • Installation/Docker/Kubernetes: references/deployment.md.
  • Configuration layering: references/configuration.md.
  • Security/auth/TLS boundary: references/security.md.
  • Backup/restore: references/snapshots.md.

API interface choice

  • REST vs gRPC, Python SDK: references/api-clients.md.

How to maintain this skill

  • Keep SKILL.md short (router + usage guidance).
  • Put details into references/*.md.
  • Merge or reorganize references when it improves discoverability.

Critical prohibitions

  • Do not ingest/quote large verbatim chunks of vendor docs; summarize in your own words.
  • Do not invent defaults not explicitly grounded in documentation; record uncertainties as TODOs.
  • Do not design backup/restore without testing a restore path.
  • Do not use NFS as the primary persistence backend (installation docs explicitly warn against it).
  • Do not expose internal cluster communication ports publicly; rely on private networking.
  • Do not use API keys/JWT over untrusted networks without TLS.
  • Do not rely on implicit runtime defaults for production; record effective configuration.

Links

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版本
最新版本元数据

版本

v2026.09.24

发布时间

Sep 24, 2026

分类

未分类

许可证

MIT

源路径

skills/qdrant

默认分支

master

最新提交

7ae8a00

Tree SHA

47f5439