What is an integration?

Overview

An integration is a protocol adapter that translates between Vikat’s unified API and provider-specific API formats. Each integration handles request transformation, response normalization, and error mapping between the external API contract and Vikat’s internal processing pipeline. Integrations enable you to utilize Vikat’s features like governance, MCP tools, load balancing, semantic caching, multi-provider support, and more, all while preserving your existing SDK-based architecture. Vikat handles all the overhead of structure conversion, requiring only a single URL change to switch from direct provider APIs to Vikat’s gateway. Vikat converts the request/response format of the provider API to the Vikat API format based on the integration used, so you don’t have to.

Quick Migration

Before (Direct Provider)

import openai

client = openai.OpenAI(
    api_key="your-openai-key"
)

After (Vikat)

import openai

client = openai.OpenAI(
    base_url="http://localhost:8080/openai",  # Point to Vikat
    api_key="dummy-key" # Keys are handled in Vikat now
)

That’s it! Your application now benefits from Vikat’s features with no other changes.

Supported Integrations

Provider-Prefixed Models

Use multiple providers seamlessly by prefixing model names with the provider:

OpenAI
Anthropic
Azure
Vertex
Ollama

import openai

# Single client, multiple providers
client = openai.OpenAI(
    base_url="http://localhost:8080/openai",
    api_key="dummy"  # API keys configured in Vikat
)

# OpenAI models
response1 = client.chat.completions.create(
    model="gpt-4o-mini", # (default OpenAI since it's OpenAI's SDK)
    messages=[{"role": "user", "content": "Hello!"}]
)

import openai

# Anthropic models using OpenAI SDK format
response2 = client.chat.completions.create(
    model="anthropic/claude-3-sonnet-20240229",
    messages=[{"role": "user", "content": "Hello!"}]
)

import openai

# Azure models
response4 = client.chat.completions.create(
    model="azure/gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}]
)

import openai

# Google Vertex models
response3 = client.chat.completions.create(
    model="vertex/gemini-pro",
    messages=[{"role": "user", "content": "Hello!"}]
)

import openai

# Local Ollama models
response5 = client.chat.completions.create(
    model="ollama/llama3.1:8b",
    messages=[{"role": "user", "content": "Hello!"}]
)

Direct API Usage

For custom HTTP clients or when you have existing provider-specific setup and want to use Vikat gateway without restructuring your codebase:

import requests

# Fully OpenAI compatible endpoint
response = requests.post(
    "http://localhost:8080/openai/v1/chat/completions",
    headers={
        "Authorization": f"Bearer {openai_key}",
        "Content-Type": "application/json"
    },
    json={
        "model": "gpt-4o-mini",
        "messages": [{"role": "user", "content": "Hello!"}]
    }
)

# Fully Anthropic compatible endpoint
response = requests.post(
    "http://localhost:8080/anthropic/v1/messages",
    headers={
        "Content-Type": "application/json",
    },
    json={
        "model": "claude-3-sonnet-20240229",
        "max_tokens": 1000,
        "messages": [{"role": "user", "content": "Hello!"}]
    }
)

# Fully Google GenAI compatible endpoint
response = requests.post(
    "http://localhost:8080/genai/v1beta/models/gemini-1.5-flash/generateContent",
    headers={
        "Content-Type": "application/json",
    },
    json={
        "contents": [
            {"parts": [{"text": "Hello!"}]}
        ],
        "generation_config": {
            "max_output_tokens": 1000,
            "temperature": 1
        }
    }
)

Listing Models

All integrations support listing available models through their respective list models endpoints (e.g., /openai/v1/models, /anthropic/v1/models). By default, list models requests return models from all configured providers in Vikat.

Filtering by Provider

You can control which provider’s models to list using the x-vikat-list-models-provider header:

Python
JavaScript
cURL

import openai

client = openai.OpenAI(
    base_url="http://localhost:8080/openai",
    api_key="dummy-key"
)

# List models from all providers (default behavior)
all_models = client.models.list()

# List models from a specific provider only
openai_models = client.models.list(
    extra_headers={
        "x-vikat-list-models-provider": "openai"
    }
)

anthropic_models = client.models.list(
    extra_headers={
        "x-vikat-list-models-provider": "anthropic"
    }
)

import OpenAI from "openai";

const openai = new OpenAI({
  baseURL: "http://localhost:8080/openai",
  apiKey: "dummy-key",
});

// List models from all providers (default behavior)
const allModels = await openai.models.list();

// List models from a specific provider only
const openaiModels = await openai.models.list({
  headers: {
    "x-vikat-list-models-provider": "openai",
  },
});

const anthropicModels = await openai.models.list({
  headers: {
    "x-vikat-list-models-provider": "anthropic",
  },
});

# List models from all providers (default)
curl http://localhost:8080/openai/v1/models

# List models from specific provider
curl http://localhost:8080/openai/v1/models \
  -H "x-vikat-list-models-provider: openai"

# Explicitly request all providers
curl http://localhost:8080/openai/v1/models \
  -H "x-vikat-list-models-provider: all"

Header Behavior

Header Value	Behavior
Not set (default)	Lists models from all configured providers
`all`	Lists models from all configured providers
`openai`	Lists models from OpenAI provider only
`anthropic`	Lists models from Anthropic provider only
`vertex`	Lists models from Vertex AI provider only
Any valid provider	Lists models from that specific provider

Response Fields

When listing models from all providers, some provider-specific fields may be empty or contain default values if the information is not available from all providers. This is normal behavior as different providers expose different model metadata.

Migration Strategies

Gradual Migration

Start with development - Test Vikat in dev environment
Canary deployment - Route 5% of traffic through Vikat
Feature-by-feature - Migrate specific endpoints gradually
Full migration - Switch all traffic to Vikat

Blue-Green Migration

import os
import random

# Route traffic based on feature flag
def get_base_url(provider: str) -> str:
    if os.getenv("USE_VIKAT", "false") == "true":
        return f"http://vikat:8080/{provider}"
    else:
        return f"https://api.{provider}.com"

# Gradual rollout
def should_use_vikat() -> bool:
    rollout_percentage = int(os.getenv("VIKAT_ROLLOUT", "0"))
    return random.randint(1, 100) <= rollout_percentage

Feature Flag Integration

# Using feature flags for safe migration
import openai
from feature_flags import get_flag

def create_client():
    if get_flag("use_vikat_openai"):
        base_url = "http://vikat:8080/openai"
    else:
        base_url = "https://api.openai.com"

    return openai.OpenAI(
        base_url=base_url,
        api_key=os.getenv("OPENAI_API_KEY")
    )

Next Steps

HTTP Transport Overview - Main HTTP transport guide
Endpoints - Complete API reference
Configuration - Provider setup and config

Overview

Quick Start

Release Cadence

Migration Guides

SDK Integrations

Providers & Guides

MCP Gateway

Custom plugins

Open Source Features

What is an integration?

Overview

Quick Migration

Before (Direct Provider)

After (Vikat)

Supported Integrations

Provider-Prefixed Models

Direct API Usage

Listing Models

Filtering by Provider

Header Behavior

Response Fields

Migration Strategies

Gradual Migration

Blue-Green Migration

Feature Flag Integration

Next Steps

​Overview

​Quick Migration

​Before (Direct Provider)

​After (Vikat)

​Supported Integrations

​Provider-Prefixed Models

​Direct API Usage

​Listing Models

​Filtering by Provider

​Header Behavior

​Response Fields

​Migration Strategies

​Gradual Migration

​Blue-Green Migration

​Feature Flag Integration

​Next Steps

Overview

Quick Migration

Before (Direct Provider)

After (Vikat)

Supported Integrations

Provider-Prefixed Models

Direct API Usage

Listing Models

Filtering by Provider

Header Behavior

Response Fields

Migration Strategies

Gradual Migration

Blue-Green Migration

Feature Flag Integration

Next Steps