Reka AI

Integrate Reka AI models with Portkey’s AI Gateway

Portkey provides a robust and secure gateway to integrate various Large Language Models (LLMs) into applications, including Reka AI’s multimodal models.

With Portkey, take advantage of features like fast AI gateway access, observability, prompt management, and more, while securely managing API keys through Model Catalog.

Quick Start

Get Reka AI working in 3 steps:

Python

from portkey_ai import Portkey

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

portkey = Portkey(api_key="PORTKEY_API_KEY")

response = portkey.chat.completions.create(
    model="@reka/reka-core",
    messages=[{"role": "user", "content": "Say this is a test"}]
)

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

import Portkey from 'portkey-ai'

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

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

const response = await portkey.chat.completions.create({
    model: "@reka/reka-core",
    messages: [{ role: "user", content: "Say this is a test" }]
})

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 @reka 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="@reka/reka-core",
    messages=[{"role": "user", "content": "Say this is a test"}]
)

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 @reka 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: "@reka/reka-core",
    messages: [{ role: "user", content: "Say this is a test" }]
})

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

# 1. Add @reka provider in model catalog
# 2. Use it:

curl https://api.portkey.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -d '{
    "model": "@reka/reka-core",
    "messages": [
      { "role": "user", "content": "Say this is a test" }
    ]
  }'

Tip: You can also set provider="@reka" in Portkey() and use just model="reka-core" in the request.

Add Provider in Model Catalog

1. Go to Model Catalog → Add Provider
2. Select Reka AI
3. Choose existing credentials or create new by entering your Reka AI API key
4. Name your provider (e.g., reka-prod)

Complete Setup Guide →

See all setup options, code examples, and detailed instructions

Managing Reka AI Prompts

Manage all prompt templates to Reka AI in the Prompt Library. All current Reka AI models are supported, and you can easily test different prompts.

Use the portkey.prompts.completions.create interface to use the prompt in an application.

Next Steps

Add Metadata

Add metadata to your Reka AI requests

Gateway Configs

Add gateway configs to your Reka AI requests

Tracing

Trace your Reka AI requests

Fallbacks

Setup fallback from OpenAI to Reka AI

For complete SDK documentation:

SDK Reference

Complete Portkey SDK documentation