This guide will help you implement enterprise-grade security, observability, and governance for OpenWebUI using Portkey. While OpenWebUI supports various provider plugins, Portkey provides a unified interface for all your LLM providers, offering comprehensive features for model management, cost tracking, observability, and metadata logging. For IT administrators deploying centralized instances of OpenWebUI, Portkey enables essential enterprise features including usage tracking, access controls, and budget management. Let’s walk through implementing these features step by step.

Understanding the Implementation

When implementing Portkey with OpenWebUI in your organization, we’ll follow these key steps:

Basic OpenWebUI integration with Portkey
Setting up organizational governance using Model Catlog
Managing user access and permissions, setting- budget & rate limits, and more…

If you’re an individual user just looking to use Portkey with Open WebUI, you only need to complete Steps 1 and 2 to get started.

1. Setting Up Portkey

Create Portkey API Key

Go to the API Keys section in the Portkey sidebar.
Click Create New API Key with all the permissions.
Save and copy the key — you’ll need it for OpenWebUI.

Add Your Provider

Navigate to Model Catalog → AI Providers.

Click Create Provider (if this is your first time using Portkey).
Select Create New Integration → choose your AI service (OpenAI, Anthropic, etc.).
Enter your provider’s API key and required details.
(Optional) Configure workspace and model provisioning.
Click Create Integration.

Get Your Model Slugs

Go to Model Catalog → Models.
Copy the slug for each model you want to use (@provider-slug/model-name).

Example: @openai-test/gpt-4o — use this in the model field of API requests.

That’s it — your Portkey setup is ready. Now let’s integrate it with OpenWebUI.

2. Integrating Portkey with OpenWebUI

Since Portkey is OpenAI API–compatible, connecting it to OpenWebUI is quick and straightforward.

You’ll need your Portkey API key from Step 1 before continuing.

Access Admin Panel

Start your OpenWebUI server.
Click on your username at the bottom left.
Go to the Admin Panel -> Settings tab -> Select Connections from the sidebar.

Enable Direct Connections

Turn ON Direct Connections and OpenAI API toggle switch.
Click the + icon next to Manage OpenAI API Connections.

Configure Portkey Connection

Fill in the following in the Edit Connection dialog:

URL: https://api.portkey.ai/v1
Key: Your Portkey API key from Step 1
Prefix ID: portkey (or any name you prefer)
Model IDs: Your model slugs (e.g., @openai/gpt-4o, @anthropic/claude-3-sonnet) from Step 1

Click Save to finish.

Select and Use Your Model

Go back to the main chat interface and select Portkey model (format: @model-name) from the dropdown at the top.
Start chatting!

For Anthropic models: You must set a Max Tokens value. Click the settings icon (top right) and set Max Tokens to a valid number (e.g., 1024).

You can track requests, usage, and costs in the Portkey Dashboard.

3. Set Up Enterprise Governance for Open WebUI

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

Cost Management: Controlling and tracking AI spending across teams
Access Control: Managing team access and workspaces
Usage Analytics: Understanding how AI is being used across the organization
Security & Compliance: Maintaining enterprise security standards
Reliability: Ensuring consistent service across all users
Model Management: Managing what models are being used in your setup

Portkey adds a comprehensive governance layer to address these enterprise Enterprise Implementation Guide

Step 1: Implement Budget Controls & Rate Limits

Step 2: Define Model Access Rules

Step 4: Set Routing Configuration

Portkey allows you to control your routing logic very simply with it’s Configs feature. Portkey Configs provide this control layer with things like:

Data Protection: Implement guardrails for sensitive code and data
Reliability Controls: Add fallbacks, load-balance, retry and smart conditional routing logic
Caching: Implement Simple and Semantic Caching. and more…

Example Configuration:

Here’s a basic configuration to load-balance requests to OpenAI and Anthropic:

{
  "strategy": {
    "mode": "load-balance"
  },
  "targets": [
    {
      "override_params": {
        "model": "@YOUR_OPENAI_PROVIDER_SLUG/gpt-model"
      }
    },
    {
      "override_params": {
        "model": "@YOUR_ANTHROPIC_PROVIDER/claude-sonnet-model"
      }
    }
  ]
}

Create your config on the Configs page in your Portkey dashboard. You’ll need the config ID for connecting to Open WebUI’s setup.

Configs can be updated anytime to adjust controls without affecting running applications.

Step 4: Implement Access Controls

Step 3: Implement Access Controls

Create User-specific API keys that automatically:

Track usage per developer/team with the help of metadata
Apply appropriate configs to route requests
Collect relevant metadata to filter logs
Enforce access permissions

Create API keys through:

Example using Python SDK:

from portkey_ai import Portkey

portkey = Portkey(api_key="YOUR_ADMIN_API_KEY")

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

For detailed key management instructions, see our API Keys documentation.

Step 5: Deploy & Monitor

Enterprise Features Now Available

Open WebUI now has:

Per-developer budget controls
Model access governance
Usage tracking & attribution
Code security guardrails
Reliability features for development workflows

Here’s the new section for image generation using Portkey with Open WebUI:

4. Image Generation with Portkey

Portkey enables seamless image generation through Open WebUI by providing a unified interface for various image generation models like DALL-E 2, DALL-E 3, and other compatible models. This integration allows you to leverage Portkey’s enterprise features including cost tracking, access controls, and observability for all your image generation needs.

Setting Up Image Generation

Before proceeding, ensure you have completed the basic Portkey setup from Step 1 and have your Portkey API key ready.

Access Image Settings

Navigate to your Open WebUI Admin Panel
Go to Settings → Images from the sidebar

Configure Image Generation Engine

In the Image Settings page, configure the following:

Enable Image Generation: Toggle ON the Image Generation (Experimental) option
Image Generation Engine: Select Default (Open AI) from the dropdown
OpenAI API Config: Enter Portkey’s base URL:
```
https://api.portkey.ai/v1
```
API Key: Enter your Portkey API key (from Step 1)
Set Default Model: Enter your model slug in the format:
```
@provider-key/model-name
```
For example: @openai-test/dall-e-3

Configure Model-Specific Settings

Choose the model you wish to use. Note that image size options will depend on the selected model:

DALL·E 2: Supports 256x256, 512x512, or 1024x1024 images.
DALL·E 3: Supports 1024x1024, 1792x1024, or 1024x1792 images.
GPT-Image-1: Supports auto, 1024x1024, 1536x1024, or 1024x1536 images.

Steps: Set the number of generation steps (typically 50 for good quality)

Other Models: Check your provider’s documentation (gemini, vertex, and more..) for supported sizes

Test Your Configuration

Return to the main chat interface
Type a prompt and click the image generation icon
Your image will be generated using Portkey’s infrastructure
Track usage and costs in the Portkey Dashboard

Monitoring Image Generation

All image generation requests through Portkey are automatically tracked with:

Cost Attribution: See exact costs per image generation
Request Logs: Full prompt and response tracking
Performance Metrics: Generation time and success rates
Metadata Tags: Track image generation by team/department

Pro Tip: If you are using a different AI provider (Gemini, Vertex AI, etc..) and you need to pass some additional params for image gen, you can do that by adding them in portkey’s config as override_params and attaching it to your Portkey API key. Here’s a guide

Portkey Features

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

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.

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…

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 model slug in your default config object.

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.

Custom Metata

5. Enterprise Access Management

Budget Controls

Set and manage spending limits across teams and departments. Control costs with granular budget limits and usage tracking.

Single Sign-On (SSO)

Enterprise-grade SSO integration with support for SAML 2.0, Okta, Azure AD, and custom providers for secure authentication.

Organization Management

Hierarchical organization structure with workspaces, teams, and role-based access control for enterprise-scale deployments.

Access Rules & Audit Logs

Comprehensive access control rules and detailed audit logging for security compliance and usage tracking.

6. Reliability Features

Fallbacks

Automatically switch to backup targets if the primary target fails.

Conditional Routing

Route requests to different targets based on specified conditions.

Load Balancing

Distribute requests across multiple targets based on defined weights.

Caching

Enable caching of responses to improve performance and reduce costs.

Smart Retries

Automatic retry handling with exponential backoff for failed requests

Budget Limits

Set and manage budget limits across teams and departments. Control costs with granular budget limits and usage tracking.

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

Guardrails

Implement real-time protection for your LLM interactions with automatic detection and filtering of sensitive content, PII, and custom security rules. Enable comprehensive data protection while maintaining compliance with organizational policies.

FAQs

Can I use multiple LLM providers with the same API key?

How do I track costs for different teams?

What happens if a team exceeds their budget limit?

Next Steps

Join our Community

For enterprise support and custom features, contact our enterprise team.

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Agents

AI Apps

Libraries

Tracing Providers

​Understanding the Implementation

​1. Setting Up Portkey

​2. Integrating Portkey with OpenWebUI

​3. Set Up Enterprise Governance for Open WebUI

​Enterprise Features Now Available

​4. Image Generation with Portkey

​Setting Up Image Generation

​Monitoring Image Generation

​Portkey Features

​1. Comprehensive Metrics

​2. Advanced Logs

​3. Unified Access to 1600+ LLMs

​4. Advanced Metadata Tracking

Custom Metata

​5. Enterprise Access Management

Budget Controls

Single Sign-On (SSO)

Organization Management

Access Rules & Audit Logs

​6. Reliability Features

Fallbacks

Conditional Routing

Load Balancing

Caching

Smart Retries

Budget Limits

​7. Advanced Guardrails

Guardrails

​FAQs

​Next Steps

Understanding the Implementation

1. Setting Up Portkey

2. Integrating Portkey with OpenWebUI

3. Set Up Enterprise Governance for Open WebUI

Enterprise Features Now Available

4. Image Generation with Portkey

Setting Up Image Generation

Monitoring Image Generation

Portkey Features

1. Comprehensive Metrics

2. Advanced Logs

3. Unified Access to 1600+ LLMs

4. Advanced Metadata Tracking

5. Enterprise Access Management

6. Reliability Features

7. Advanced Guardrails

FAQs

Next Steps