Open WebUI
Cost tracking, observability, and more for Open WebUI
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 Virtual Keys and Configs
- Managing user access and permissions
If you’re an individual user just looking to use Portkey with OpenWebUI, you only need to complete Steps 1 and 2 to get started.
1. Basic Integration
Let’s start by integrating Portkey with your OpenWebUI installation. This integration uses OpenWebUI’s pipeline functionality to route all requests through Portkey’s Platform.
Installing the Portkey Plugin
- Start your OpenWebUI server
- Navigate to
Workspace
and then go to theFunctions
section - Click on the
+
button in UI - Copy and paste the Portkey plugin code
2. Setting Up Portkey Pipeline
To use OpenWebUI with Portkey, you’ll need to configure three key components:
Portkey API Key: Get your Portkey API key from here. You’ll need this for authentication with Portkey’s services.
Virtual Keys: Virtual Keys are Portkey’s secure way to manage your LLM provider API keys. They provide essential controls like:
- Budget limits for API usage
- Rate limiting capabilities
- Secure API key storage
Craeate a Virtual Key in your Portkey dashboard and save it for future use.
For detailed information on budget limits, refer to this documentation
Using Configs (Optional): Configs in Portkey enhance your implementation with features like advanced routing, fallbacks, and retries. Here’s a simple config example that implements 5 retry attempts on server errors:
You can create and store these configs in Portkey’s config library. This can later be accessed on using the Config Slug in Open WebUI.
Configs are highly flexible and can be customized for various use cases. Learn more in our Configs documentation.
3. Configure Pipeline Variables
The pipeline setup involves configuring both credentials and model access in OpenWebUI.
Credentials Setup:
- In OpenWebUI, navigate to
Workspace
→Functions
- Click the
Valves
button to open the configuration interface - Add the following credentials:
- Your Portkey API Key
- Config slug (if using Configs)
- Base URL (only needed for Open Source Gateway users)
Model Configuration
- In the Functions section, click the
...
button and selectEdit
- Find the virtual keys JSON object in the Portkey function code
- Update it with your virtual keys:
- Configure model names in the pipe function in this format:
Example:
perplexity-ai
is correct. perplexity
is wrong4. Set Up Enterprise Governance for OpenWebUI
Why Enterprise Governance? If you are using OpenWeb UI 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
Enterprise Features Now Available
OpenWeb UI now has:
- Departmental budget controls
- Model access governance
- Usage tracking & attribution
- Security guardrails
- Reliability features
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 virtual key
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
Next Steps
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For enterprise support and custom features, contact our enterprise team.
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