Jina AI

Use Jina AI’s embedding and reranker models through Portkey.

Quick Start

Get started with Jina AI in under 2 minutes:

Python

from portkey_ai import Portkey

# 1. Install: pip install portkey-ai
# 2. Add @jina provider in model catalog
# 3. Use it:

portkey = Portkey(api_key="PORTKEY_API_KEY")

response = portkey.chat.completions.create(
    model="@jina/jina-embeddings-v2-base-en",
    messages=[{"role": "user", "content": "Hello!"}]
)

print(response.choices[0].message.content)

import Portkey from 'portkey-ai'

// 1. Install: npm install portkey-ai
// 2. Add @jina provider in model catalog
// 3. Use it:

const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY"
})

const response = await portkey.chat.completions.create({
    model: "@jina/jina-embeddings-v2-base-en",
    messages: [{ role: "user", content: "Hello!" }]
})

console.log(response.choices[0].message.content)

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL

# 1. Install: pip install openai portkey-ai
# 2. Add @jina provider in model catalog
# 3. Use it:

client = OpenAI(
    api_key="PORTKEY_API_KEY",  # Portkey API key
    base_url=PORTKEY_GATEWAY_URL
)

response = client.chat.completions.create(
    model="@jina/jina-embeddings-v2-base-en",
    messages=[{"role": "user", "content": "Hello!"}]
)

print(response.choices[0].message.content)

import OpenAI from "openai"
import { PORTKEY_GATEWAY_URL } from "portkey-ai"

// 1. Install: npm install openai portkey-ai
// 2. Add @jina provider in model catalog
// 3. Use it:

const client = new OpenAI({
    apiKey: "PORTKEY_API_KEY",  // Portkey API key
    baseURL: PORTKEY_GATEWAY_URL
})

const response = await client.chat.completions.create({
    model: "@jina/jina-embeddings-v2-base-en",
    messages: [{ role: "user", content: "Hello!" }]
})

console.log(response.choices[0].message.content)

curl https://api.portkey.ai/v1/embeddings \
    -H "Content-Type: application/json" \
    -H "x-portkey-api-key: $PORTKEY_API_KEY" \
    -H "x-portkey-provider: @jina" \
    -d '{
        "model": "jina-embeddings-v2-base-en",
        "input": "embed this text"
    }'

Add Provider in Model Catalog

Before making requests, add Jina AI to your Model Catalog:

1. Go to Model Catalog → Add Provider
2. Select Jina AI
3. Enter your Jina AI API key
4. Name your provider (e.g., jina)

Complete Setup Guide

See all setup options and detailed configuration instructions

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Jina AI Capabilities

Embeddings

Generate embeddings with language-specific models:

Python

from portkey_ai import Portkey

portkey = Portkey(api_key="PORTKEY_API_KEY", provider="@jina")

embeddings = portkey.embeddings.create(
    model="jina-embeddings-v2-base-en",
    input="embed this text"
)

print(embeddings.data[0].embedding)

import Portkey from 'portkey-ai';

const portkey = new Portkey({
    apiKey: 'PORTKEY_API_KEY',
    provider: '@jina'
});

const embeddings = await portkey.embeddings.create({
    model: "jina-embeddings-v2-base-en",
    input: "embed this text"
});

console.log(embeddings.data[0].embedding);

Reranking

Rerank documents for better search results:

cURL

curl https://api.portkey.ai/v1/rerank \
    -H "Content-Type: application/json" \
    -H "x-portkey-api-key: $PORTKEY_API_KEY" \
    -H "x-portkey-provider: @jina" \
    -d '{
        "model": "jina-reranker-v1-base-en",
        "query": "Organic skincare products for sensitive skin",
        "documents": [
            "Eco-friendly kitchenware for modern homes",
            "Biodegradable cleaning supplies for eco-conscious consumers",
            "Organic cotton baby clothes for sensitive skin"
        ],
        "top_n": 2
    }'

from portkey_ai import Portkey

portkey = Portkey(api_key="PORTKEY_API_KEY", provider="@jina")

response = portkey.post(
    "/rerank",
    model="jina-reranker-v1-base-en",
    query="Organic skincare products for sensitive skin",
    documents=[
        "Eco-friendly kitchenware for modern homes",
        "Biodegradable cleaning supplies for eco-conscious consumers",
        "Organic cotton baby clothes for sensitive skin"
    ],
    top_n=2
)

print(response)

import Portkey from 'portkey-ai';

const portkey = new Portkey({
    apiKey: 'PORTKEY_API_KEY',
    provider: '@jina'
});

const response = await portkey.post(
    "/rerank",
    {
        model: "jina-reranker-v1-base-en",
        query: "Organic skincare products for sensitive skin",
        documents: [
            "Eco-friendly kitchenware for modern homes",
            "Biodegradable cleaning supplies for eco-conscious consumers",
            "Organic cotton baby clothes for sensitive skin"
        ],
        top_n: 2
    }
);

console.log(response);

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Supported Models

Jina AI provides embedding models in multiple languages:

Model Family	Languages	Description
jina-embeddings-v2-base	en, de, es, zh, and more	Multilingual embeddings
jina-reranker-v1-base	en, de, es, zh	Reranking models

Check Jina AI’s model page for the complete list.

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Next Steps

Gateway Configs

Add fallbacks, load balancing, and more

Observability

Monitor and trace your Jina AI requests

Caching

Cache embeddings for faster responses

Metadata

Add custom metadata to requests

For complete SDK documentation:

SDK Reference

Complete Portkey SDK documentation