Qdrant

Qdrant is an open-source vector similarity search engine built for production-ready vector search applications. It provides a convenient API to store, search, and manage vectors with additional payload data. The Prisma AIRS AI Gateway provides a proxy to Qdrant - you can log your Qdrant requests and manage auth for Qdrant clusters on the AI Gateway.

Using Qdrant with the AI Gateway

The AI Gateway provides a consistent API to interact with models from various providers. To integrate Qdrant with the AI Gateway:

1. Install the OpenAI SDK

Add the OpenAI SDK to your application to interact with Qdrant through the AI Gateway.

NodeJS
Python

npm install openai --save

pip install openai

2. Create a New Integration

To use Qdrant with the AI Gateway, get your API key from Qdrant App, then add it to the AI Gateway to create Qdrant integration. You will also need your AI Gateway API Key from the AI Gateway’s Dashboard.

OpenAI Python SDK
OpenAI Node SDK

from openai import OpenAI

client = OpenAI(
    api_key="PORTKEY_API_KEY",
    base_url="https://aigw.portkey.ai/v1",
    default_headers={
        "x-portkey-provider": "qdrant",
        "x-portkey-custom-host": "QDRANT_HOST",  # Replace with your Qdrant host
    }
)

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "PORTKEY_API_KEY",
  baseURL: "https://aigw.portkey.ai/v1",
  defaultHeaders: {
      "x-portkey-provider": "qdrant",
      "x-portkey-custom-host": "QDRANT_HOST",  // Replace with your Qdrant host
  },
});

3. Use the OpenAI SDK to interact with Qdrant

cURL
OpenAI NodeJS
OpenAI Python

curl --location --request POST 'https://xxxx-xxx-xxx-xx-xxxxxx.us-west-2-0.aws.cloud.qdrant.io' \
--header 'x-portkey-custom-host: QDRANT_HOST' \
--header 'x-portkey-provider: QDRANT_PROVIDER' \
--header 'Authorization: Bearer PORTKEY_API_KEY'

import OpenAI from 'openai';

const gateway = new OpenAI({
  apiKey: "PORTKEY_API_KEY",
  baseURL: "https://aigw.portkey.ai/v1",
  defaultHeaders: {
      "x-portkey-provider": "@QDRANT_PROVIDER",
      "x-portkey-custom-host": "QDRANT_HOST",  // Replace with your Qdrant host
  }
});

async function makeRequest() {
    const response = await gateway.post(
      "https://xxxx-xxx-xxx-xx-xxxxxx.us-west-2-0.aws.cloud.qdrant.io",
      { /* Your request body here */ }
    );
    console.log(response);
}

makeRequest();

from openai import OpenAI

openai = OpenAI(
    api_key="PORTKEY_API_KEY",
    base_url="https://aigw.portkey.ai/v1",
    default_headers={
        "x-portkey-provider": "qdrant",
        "x-portkey-custom-host": "QDRANT_HOST",  # Replace with your Qdrant host
    }
)

response = openai.post(
    url="https://xxxx-xxx-xxx-xx-xxxxxx.us-west-2-0.aws.cloud.qdrant.io", # Qdrant search endpoint, You can use any Qdrant endpoint
)

print(response)

Last modified on September 15, 2026

Integrations

LLM Integrations

Cloud Platforms

Guardrails

Plugins

Vector Databases

Agents

AI Apps

Libraries

Tracing Providers

MCP Clients

MCP Servers

Using Qdrant with the AI Gateway

1. Install the OpenAI SDK

2. Create a New Integration

3. Use the OpenAI SDK to interact with Qdrant

​Using Qdrant with the AI Gateway

​1. Install the OpenAI SDK

​2. Create a New Integration

​3. Use the OpenAI SDK to interact with Qdrant

Using Qdrant with the AI Gateway

1. Install the OpenAI SDK

2. Create a New Integration

3. Use the OpenAI SDK to interact with Qdrant