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qdrant-clients-sdk

qdrant-clients-sdk

github.com/qdrantData & databases2651.8k installsUpdated 1d ago
Repository

About qdrant-clients-sdk

A skill for finding Qdrant client SDK documentation and code examples across six languages. It covers supported SDKs and APIs, and describes a snippet search endpoint for locating examples by language and use case.

Key features

  1. 01Lists supported client SDKs
  2. 02Covers six programming languages
  3. 03Describes REST and gRPC APIs
  4. 04Searches curated code snippets
  5. 05Supports Markdown or JSON snippets

Use cases

  1. 01Choosing a Qdrant SDK
  2. 02Looking up a client installation command
  3. 03Finding code for a Qdrant task
  4. 04Retrieving examples in JSON format

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/qdrant/skills --skill qdrant-clients-sdk

After installing, type/qdrant-clients-sdkin Claude Code to confirm it loaded.

Details

From the project README

Qdrant Clients SDK

Qdrant has the following officially supported client SDKs:

API Reference

All interaction with Qdrant can happen through the REST API or gRPC API. We recommend using the REST API if you are using Qdrant for the first time or working on a prototype.

Code examples

To obtain code examples for a specific client and use case, you can send a search request to the library of curated code snippets for the Qdrant client.

curl -X GET "https://skills.qdrant.tech/snippets/search?language=python&query=how+to+upload+points"

Available languages: python, typescript, rust, java, go, csharp

Response example:


## Snippet 1

*qdrant-client* (vlatest) — https://skills.qdrant.tech/md/documentation/manage-data/points/

Uploads multiple vector-embedded points to a Qdrant collection using the Python qdrant_client (PointStruct) with id, payload (e.g., color), and a 3D-like vector for similarity search. It supports parallel uploads (parallel=4) and a retry policy (max_retries=3) for robust indexing. The operation is idempotent: re-uploading with the same id overwrites existing points; if ids aren’t provided, Qdrant auto-generates UUIDs.

client.upload_points(
    collection_name="{collection_name}",
    points=[
        models.PointStruct(
            id=1,
            payload={
                "color": "red",
            },
            vector=[0.9, 0.1, 0.1],
        ),
        models.PointStruct(
            id=2,
            payload={
                "color": "green",
            },
            vector=[0.1, 0.9, 0.1],
        ),
    ],
    parallel=4,
    max_retries=3,
)

Default response format is markdown, if snippet output is required in JSON format, you can add &format=json to the query string.

Comments

Markdown supported