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Portkey Key

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Comprehensive documentation for Portkey's AI Gateway, Guardrails, Observability, Prompts, and Governance features.

Portkey Docs

Portkey AI is a comprehensive platform designed to streamline and enhance AI integration for developers and organizations. It serves as a unified interface for interacting with over 250 AI models, offering advanced tools for control, visibility, and security in your Generative AI apps.

What is Portkey?

Integrate Portkey and analyze your first LLM call in 2 minutes!

Make Your First Request

Portkey Features

Automatically create, manage, and execute fine-tuning jobs for Large Language Models (LLMs) across multiple providers.

Autonomous Fine-tuning

Open Source

Comparing Portkey's Open-source version and Dev, Pro, Enterprise plans.

Feature Comparison

Contact Us

Are you navigating the challenging journey of transitioning LLMs from prototype stages to full-scale production? You're not alone. As this frontier of technology continues to expand, the roadmap isn't always clear. Best practices, guidelines, and efficient methodologies are still on the horizon.

Developer Forum

Since Portkey functions as a gateway - you may encounter Portkey-related, as well as non-Portkey related erros while using our services.

Common Errors & Resolutions

December '23 Migration

Integrations

Submit an Integration

Portkey connects with all major LLM providers and orchestration frameworks.

Overview

Google Gemini

Route to your AWS Sagemaker models through Portkey

AWS SageMaker

Ollama

Integrate your privately hosted LLMs with Portkey for unified management, observability, and reliability.

Bring Your Own LLM

Transform offline LLMs into online models with real-time internet search capabilities.

Exa Online Search

Milvus

Qdrant

Portkey helps bring your agents to production

Use Portkey with Autogen to take your AI Agents to production

Autogen

Use Portkey with Control Flow to take your AI Agents to production

Control Flow

Use Portkey with CrewAI to take your AI Agents to production

CrewAI

Langchain Agents

Use Portkey with LangGraph to take your AI Agents to production

LangGraph Agents

Use Portkey with Llama Agents to take your AI Agents to production

Llama Agents by Llamaindex

The Portkey x Swarm integration brings advanced AI gateway capabilities, full-stack observability, and reliability features to build production-ready AI agents.

OpenAI Swarm

Use Portkey with Phidata to take your AI Agents to production

Phidata

You can also use Portkey if you are doing custom agent orchestration!

Bring Your own Agents

AutoGen is a framework that enables the development of LLM applications using multiple agents that can converse with each other to solve tasks.

Integrate DSPy with Portkey for production-ready LLM pipelines

DSPy

With Portkey, you can confidently take your Instructor pipelines to production and get complete observability over all of your calls + make them reliable - all with a 2 LOC change!

Instructor

Add usage tracking, cost controls, and security guardrails to your n8n workflows

Portkey adds core production capabilities to any Langchain app.

Langchain (Python)

Langchain (JS/TS)

Cost tracking, observability, and more for LibreChat

LibreChat

Cost tracking, observability, and more for Open WebUI

Open WebUI

Add usage tracking, cost controls, and security guardrails to your Jan deployment

Add usage tracking, cost controls, and security guardrails to your Codex CLI deployment

OpenAI Codex CLI

Add usage tracking, cost controls, and security guardrails to your Anything LLM deployment

Anything LLM

The **Portkey x LlamaIndex** integration brings advanced **AI gateway** capabilities, full-stack **observability**, and **prompt management** to apps built on LlamaIndex.

LlamaIndex (Python)

Portkey brings advanced **AI gateway** capabilities, full-stack **observability**, and **prompt management** + **versioning** to your **Promptfoo** projects. This document provides an overview of how to leverage the strengths of both the platforms to streamline your AI development workflow.

Promptfoo

Integrate Portkey with Vercel AI SDK for production-ready and reliable AI apps

Vercel

Integrate MindsDB with Portkey to build enterprise-grade AI use-cases

MindsDb

ToolJet is a low-code platform that lets you build apps by connecting APIs and data sources, with Portkey integration adding AI features like chat interfaces and automation.

ToolJet

MongoDB

Supabase

Learn how to integrate Portkey's enterprise features with Zed for enhanced observability, reliability and governance.

Learn how to integrate Portkey's enterprise features with any OpenAI Compliant project for enhanced observability, reliability and governance.

Portkey with Any OpenAI Compatible Project

Microsoft Semantic Kernel

This documentation provides detailed information about the various ways you can access and interact with Portkey - **a robust AI gateway** designed to simplify and enhance your experience with Large Language Models (LLMs) like OpenAI's GPT models. 

Introduction

Authentication

Header requirements and options for the Portkey API

Headers

Errors

Supported Providers

Chat

Create a Response

Get a Response

Delete a Response

List Input Items

Execute your saved prompt templates on Portkey


Prompt Completions

Renders a prompt template with its variable values filled in


Prompt Render

Insert a Log

This endpoint allows users to submit feedback for a particular interaction or response.

Create Feedback

This endpoint allows users to update existing feedback.

Update Feedback

Embeddings

Create Image

Create Image Edit

Create Image Variation

Create Speech

Create Transcription

Create Translation

Access any custom provider endpoint through Portkey API

Gateway to Other APIs

Completions

Moderations

Create Fine-tuning Job

List Fine-tuning Jobs

Retrieve Fine-tuning Job

List Fine-tuning Events

List Fine-tuning Checkpoints

Cancel Fine-tuning

Create Batch

List Batch

Retrieve Batch

Cancel Batch

Upload File

List Files

Retrieve File

Retrieve File Content

Delete File

Manage your Portkey organization and workspaces programmatically

Create Config

List Configs

Retrieve Config

Update Config

Delete Config

Create Virtual Key

List Virtual Key

Retrieve Virtual Key

Update Virtual Key

Delete Virtual Key

Create Prompt

List Prompts

Retrieve Prompt

Update Prompt

Publish Prompt

List Prompt Versions

Retrieve Prompt Version

Update Prompt Version

Update API Key

Create API Key

Delete an API Key

Retrieve an API Key

List API Key

Retrieve a user

Retrieve all users

Update a user

Remove a user

Send an invite to user for your organization

Invite a User

Retrieve an user invite

Retrieve all user invite

Delete a user invite

Resend an invite to user for your organization

Resend a user invite

Create Workspace

Retrieve all Workspaces

Retrieve a Workspace

Update Workspace

Delete a Workspace

Add a Workspace Member

Retrieve all Workspace Member

Retrieve a Workspace Member

Update Workspace Member

Remove Workspace Member

List Audit Logs

OpenAPI Specification

Building a sophisticated AI SDR agent leveraging internet search and evals to draft personalized outreach emails in 15 seconds

Ultimate AI SDR

Portkey's prompt templates offer a powerful solution for testing and building chatbots.

Build a chatbot using Portkey's Prompt Templates

Building an LLM-as-a-Judge System for AI (Customer Support) Agent

Optimizing Prompts for Customer Support using Portkey | LLama Prompt Ops Integration

A/B testing with large language models in production is crucial for driving optimal performance and user satisfaction.

A/B Test Prompts and Models

LLMs are **costly** to run. As their usage increaases, the providers have to balance serving user requests v/s straining their GPU resources too thin. They generally deal with this by putting _rate limits_ on how many requests a user can send in a minute or in a day.

Tackling Rate Limiting

Get the LLM to interact with external APIs!

Function Calling

Image Generation

Getting started with AI Gateway

Llama 3 on Groq

If you have multiple users of your GenAI app triggering the same or similar queries to your models, fetching LLM response from the models can be slow and expensive.

Return Repeat Requests from Cache

Trigger Automatic Retries on LLM Failures

You are likely familiar with how to make an API call to GPT4 for chat completions. 

API Reference

Configs

Virtual Keys

Prompts

API Keys

Analytics [BETA]

Users

User Invites

Workspaces

Workspace Members

Audit Logs

OpenAPI

Delete Prompt

Authorizations

Path Parameters

Response