Portkey natively integrates with LibreChat and makes your LibreChat deployments production-grade and reliable with our suite of features:

• Unified AI Gateway - Single interface for 1600+ LLMs with API key management. (not just OpenAI & Anthropic)
• Centralized AI observability: Real-time usage tracking for 40+ key metrics and logs for every request
• Governance - Real-time spend tracking, set budget limits and RBAC in your LibreChat setup
• Security Guardrails - PII detection, content filtering, and compliance controls

This guide will walk you through integrating Portkey with LibreChat and setting up essential enterprise features including usage tracking, access controls, and budget management.

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1. Setting up Portkey

Portkey allows you to use 1600+ LLMs with your LibreChat setup, with minimal configuration required. Let’s set up the core components in Portkey that you’ll need for integration.

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2. Integrate Portkey with LibreChat

Create the docker-compose-override.yaml file

Create this file following the instructions here. This file will point to the librechat.yaml file where we will configure our Portkey settings (in Step 3).

services:
  api:
    volumes:
    - type: bind
      source: ./librechat.yaml
      target: /app/librechat.yaml

Configure the .env file

Edit your existing .env file at the project root (if the file does not exist, copy the .env.example file and rename to .env). We will add:

PORTKEY_API_KEY=YOUR_PORTKEY_API_KEY
PORTKEY_BASE_URL=https://api.portkey.ai/v1

Edit the librechat.yaml file

Edit this file following the instructions here. Here, you can either pass your Config (containing provider/model configurations) or direct provider Virtual key saved on Portkey.

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3. Set Up Enterprise Governance for LibreChat

Why Enterprise Governance? If you are using LibreChat inside your orgnaization, you need to consider several governance aspects:

• Cost Management: Controlling and tracking AI spending across teams
• Access Control: Managing which teams can use specific models
• Usage Analytics: Understanding how AI is being used across the organization
• Security & Compliance: Maintaining enterprise security standards
• Reliability: Ensuring consistent service across all users

Portkey adds a comprehensive governance layer to address these enterprise needs. Let’s implement these controls step by step.

Enterprise Implementation Guide

{
	"strategy": {
		"mode": "single"
	},
	"targets": [
		{
			"virtual_key": "YOUR_OPENAI_VIRTUAL_KEY",
			"override_params": {
				"model": "gpt-4o"
			}
		}
	]
}

from portkey_ai import Portkey

portkey = Portkey(api_key="YOUR_ADMIN_API_KEY")

api_key = portkey.api_keys.create(
    name="engineering-team",
    type="organisation",
    workspace_id="YOUR_WORKSPACE_ID",
    defaults={
        "config_id": "your-config-id",
        "metadata": {
            "environment": "production",
            "department": "engineering"
        }
    },
    scopes=["logs.view", "configs.read"]
)

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Portkey Features

Now that you have enterprise-grade LibreChat setup, let’s explore the comprehensive features Portkey provides to ensure secure, efficient, and cost-effective AI operations.

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1. Comprehensive Metrics

Using Portkey you can track 40+ key metrics including cost, token usage, response time, and performance across all your LLM providers in real time. You can also filter these metrics based on custom metadata that you can set in your configs. Learn more about metadata here.

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2. Advanced Logs

Portkey’s logging dashboard provides detailed logs for every request made to your LLMs. These logs include:

• Complete request and response tracking
• Metadata tags for filtering
• Cost attribution and much more…

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3. Unified Access to 1600+ LLMs

You can easily switch between 1600+ LLMs. Call various LLMs such as Anthropic, Gemini, Mistral, Azure OpenAI, Google Vertex AI, AWS Bedrock, and many more by simply changing the virtual key in your default config object.

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4. Advanced Metadata Tracking

Using Portkey, you can add custom metadata to your LLM requests for detailed tracking and analytics. Use metadata tags to filter logs, track usage, and attribute costs across departments and teams.

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5. Enterprise Access Management

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6. Reliability Features

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7. Advanced Guardrails

Protect your Project’s data and enhance reliability with real-time checks on LLM inputs and outputs. Leverage guardrails to:

• Prevent sensitive data leaks
• Enforce compliance with organizational policies
• PII detection and masking
• Content filtering
• Custom security rules
• Data compliance checks

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FAQs

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Next Steps

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