Roo is an AI coding assistant that integrates directly into your VS Code environment, providing autonomous coding capabilities. While Roo offers powerful AI assistance for development tasks, Portkey adds essential enterprise controls for production deployments:

• Unified AI Gateway - Single interface for 1600+ LLMs with API key management
• 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 Roo setup
• Security Guardrails - PII detection, content filtering, and compliance controls

This guide will walk you through integrating Portkey with Roo 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 250+ LLMs with your Roo setup, with minimal configuration required. Let’s set up the core components in Portkey that you’ll need for integration.

1

Create Virtual Key

Virtual Keys are Portkey’s secure way to manage your LLM provider API keys. Think of them like disposable credit cards for your LLM API keys, providing essential controls like:

• Budget limits for API usage
• Rate limiting capabilities
• Secure API key storage

To create a virtual key: Go to Virtual Keys in the Portkey App. Save and copy the virtual key ID

Save your virtual key ID - you’ll need it for the next step.

2

Create Default Config

Configs in Portkey are JSON objects that define how your requests are routed. They help with implementing features like advanced routing, fallbacks, and retries.

We need to create a default config to route our requests to the virtual key created in Step 1.

To create your config:

1. Go to Configs in Portkey dashboard
2. Create new config with:
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   {
       "virtual_key": "YOUR_VIRTUAL_KEY_FROM_STEP1",
       "override_params": {
         "model": "gpt-4o" // Your preferred model name
       }
   }
   

3. Save and note the Config name for the next step

This basic config connects to your virtual key. You can add more advanced portkey features later.

3

Configure Portkey API Key

Now create Portkey API key access point and attach the config you created in Step 2:

1. Go to API Keys in Portkey and Create new API key
2. Select your config from Step 2
3. Generate and save your API key

Save your API key securely - you’ll need it for Roo integration.

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2. Integrate Portkey with Roo

Now that you have your Portkey components set up, let’s connect them to Roo. Since Portkey provides OpenAI API compatibility, integration is straightforward and requires just a few configuration steps in your VS Code settings.

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Opening Roo Settings

1. Open VS Code with Roo installed
2. Click on the Roo icon in your github activity bar
3. Click on the settings gear icon ⚙️ in the Roo tab

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Method 1: Using Default Config (Recommended)

This method uses the default config you created in Portkey, making it easier to manage model settings centrally.

1. In the Roo settings, navigate to Providers
2. Configure the following settings:
   • API Provider: Select OpenAI Compatible
   • Base URL: https://api.portkey.ai/v1
   • OpenAI API Key: Your Portkey API key from the setup
   • Model: dummy (since the model is defined in your Portkey config)

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Method 2: Using Custom Headers

If you prefer more direct control or need to use multiple providers dynamically, you can pass Portkey headers directly:

1. Configure the basic settings as in Method 1:

   • API Provider: OpenAI Compatible
   • Base URL: https://api.portkey.ai/v1
   • API Key: Your Portkey API key
   • Model ID: Your desired model (e.g., gpt-4o, claude-3-opus-20240229)

2. Add custom headers by clicking the + button in the Custom Headers section:

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   x-portkey-virtual-key: YOUR_VIRTUAL_KEY
   

   Optional headers:

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   x-portkey-provider: google  // Only if not using virtual key
   x-portkey-config: YOUR_CONFIG_ID  // For additional config
   

You can now use Roo with all of Portkey’s enterprise features enabled. Monitor your requests and usage in the Portkey Dashboard.

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3. Set Up Enterprise Governance for Roo

Why Enterprise Governance? When deploying Roo across development teams in your organization, you need to consider several governance aspects:

• Cost Management: Controlling and tracking AI spending across developers
• Access Control: Managing which teams can use specific models
• Usage Analytics: Understanding how AI is being used in development workflows
• Security & Compliance: Protecting sensitive code and maintaining security standards
• Reliability: Ensuring consistent service across all developers

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

Enterprise Implementation Guide

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Portkey Features

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

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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. Filter these metrics by developer, team, or project using custom metadata.

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2. Advanced Logs

Portkey’s logging dashboard provides detailed logs for every request made by Roo. These logs include:

• Complete request and response tracking
• Code context and generation metrics
• Developer attribution
• Cost breakdown per coding session

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3. Unified Access to 250+ LLMs

Easily switch between 250+ LLMs for different coding tasks. Use GPT-4 for complex architecture decisions, Claude for detailed code reviews, or specialized models for specific languages - all through a single interface.

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4. Advanced Metadata Tracking

Track coding patterns and productivity metrics with custom metadata:

• Language and framework usage
• Code generation vs completion tasks
• Time-of-day productivity patterns
• Project-specific metrics

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5. Enterprise Access Management

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6. Reliability Features

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7. Advanced Guardrails

Protect your codebase and enhance security with real-time checks on AI interactions:

• Prevent exposure of API keys and secrets
• Block generation of malicious code patterns
• Enforce coding standards and best practices
• Custom security rules for your organization
• License compliance checks

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FAQs

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Next Steps

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