Cline

Add enterprise-grade observability, cost tracking, and governance to your Cline AI coding assistant

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

• Unified AI Gateway - Single interface for 250+ 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 Cline setup
• Security Guardrails - PII detection, content filtering, and compliance controls

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

If you are an enterprise looking to standardize Cline usage across your development teams, check out this section.

1. Setting up Portkey

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

1. Create an Integration

   Navigate to the Integrations section on Portkey’s Sidebar. This is where you’ll connect your LLM providers.

   1. Find your preferred provider (e.g., OpenAI, Anthropic, etc.)
   2. Click Connect on the provider card
   3. In the “Create New Integration” window:
      • Enter a Name for reference
      • Enter a Slug for the integration
      • Enter your API Key and other provider specific details for the provider
   4. Click Next Step

   

   In your next step you’ll see workspace provisioning options. You can select the default “Shared Team Workspace” if this is your first time OR chose your current one.

2. Configure Models

   On the model provisioning page:

   • Leave all models selected (or customize)
   • Toggle Automatically enable new models if desired

   Click Create Integration to complete the integration

   
3. Copy the Provider Slug

   Once your Integration is created:

   1. Go to Model Catalog → Models tab
   2. Find and click on you your model button (if your model is not visible, you need to edit your integration from the last step)
   3. Copy the slug (e.g., @openai-dev/gpt-4o)

   We recommend clicking the Run Test Request button on this step to verify your integration. If you see the error: You do not have enough permissions to execute this request, you’ll need to create a User API Key for this step to work properly.

   You can create one here. You should be able to see simple chat request output on this step.

   

   This is your unique identifier - you’ll need it for the next step. This slug is basically @your-provider-slug/your-model-name

4. Create Default Config

   Portkey’s config is a JSON object used to define routing rules for requests to your gateway. You can create these configs in the Portkey app and reference them in requests via the config ID. For this setup, we’ll create a simple config using your provider (OpenAI) and model (gpt-4o).

   1. Go to Configs in Portkey dashboard
   2. Create new config with:
      {
          "override_params": {
            "model": "@YOUR_SLUG-FROM-LAST_STEP" // example: @openai-test/gpt-4o-mini
          }
      }
      

   3. Save and note the Config ID & Name for the next step

   
5. Configure Portkey API Key

   Finally, create a Portkey API key:

   1. Go to API Keys in Portkey
   2. Create new API key
   3. Select the config that you create from previous step
   4. Generate and save your API key

   

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

🎉 Voila, Setup complete! You now have everything needed to integrate Portkey with your application.

2. Integrate Portkey with Cline

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

You need your Portkey API Key from Step 1 before going further.

Opening Cline Settings

1. Open VS Code with Cline installed
2. Press Cmd/Ctrl + Shift + P to open the command palette
3. Search for Cline: Open in new tab
4. Click on the settings gear icon ⚙️ in the Cline tab

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

Using a default config with override_params is recommended as it allows you to manage all model settings centrally in Portkey, reducing maintenance overhead.

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 (without default config attached to portkey API key, like we did in Step 1)
   • Model ID: Your desired model slug from Step 1 (e.g., @openai-dev/gpt-4o, @anthropic-test/claude-3-opus-20240229)

2. Custom headers give you flexibility to add specific portkey functionality. Add custom headers by clicking “Add Header” and include:

Optional headers:

x-portkey-config: YOUR_CONFIG_ID  // For additional config

Using this header you can use portkey’s config for routing rules as well.

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

3. Set Up Enterprise Governance for CLine

Why Enterprise Governance? If you are using CLine 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 1: Implement Budget Controls & Rate Limits

Model Catalog enables you to have granular control over LLM access at the team/department level. This helps you:

• Set up budget limits
• Prevent unexpected usage spikes using Rate limits
• Track departmental spending

Setting Up Department-Specific Controls:

1. Navigate to Model Catalog in Portkey dashboard
2. Create new Provider for each engineering team with budget limits and rate limits
3. Configure department-specific limits

Step 2: Define Model Access Rules

Step 2: Define Model Access Rules

As your AI usage scales, controlling which teams can access specific models becomes crucial. You can simply manage AI models in your org by provisioning model at the top integration level.

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 Cline’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:

• Portkey App
• API Key Management API

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

Step 4: Deploy & Monitor

After distributing API keys to your engineering teams, your enterprise-ready Cline setup is ready to go. Each developer can now use their designated API keys with appropriate access levels and budget controls. Apply your governance setup using the integration steps from earlier sections Monitor usage in Portkey dashboard:

• Cost tracking by engineering team
• Model usage patterns for AI agent tasks
• Request volumes
• Error rates and debugging logs

Enterprise Features Now Available

Cline now has:

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

Portkey Features

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

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.

2. Advanced Logs

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

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

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.

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

Custom Metadata

5. Enterprise Access Management

Budget Controls

Set and manage spending limits per developer or team. Prevent budget overruns with automatic cutoffs.

Single Sign-On (SSO)

Enterprise-grade SSO integration for seamless developer onboarding and offboarding.

Organization Management

Hierarchical structure with teams, projects, and role-based access control for development organizations.

Access Rules & Audit Logs

Comprehensive audit logging for security compliance and code generation tracking.

6. Reliability Features

Fallbacks

Automatically switch between models if one fails, ensuring uninterrupted coding.

Conditional Routing

Route requests based on code complexity or language requirements.

Load Balancing

Distribute requests across multiple API keys or providers.

Caching

Cache common code patterns to reduce costs and improve response times.

Smart Retries

Automatic retry handling for failed requests with exponential backoff.

Budget Limits

Enforce spending limits to control development costs.

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

Guardrails

Implement real-time protection for your development environment with automatic detection and filtering of sensitive code, credentials, and security vulnerabilities.

FAQs

How do I update my Provider Budget and Rate limits after creation?

You can update your AI Providers limits at any time from the Portkey dashboard.

1. Go to Model Catalog section
2. Click on the AI Provider you want to modify
3. Update the budget or rate limits
4. Save your changes

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

Yes! You can create multiple Integrations (one for each provider) and attach them to a single config. This config can then be connected to your API key, allowing you to use multiple providers through a single API key.

How do I track costs for different teams?

Portkey provides several ways to track team costs:

• Create separate AI Providers for each team
• Use metadata tags in your configs
• Set up team-specific API keys
• Monitor usage in the analytics dashboard

What happens if a team exceeds their budget limit?

When a team reaches their budget limit:

1. Further requests will be blocked
2. Team admins receive notifications
3. Usage statistics remain available in dashboard
4. Limits can be adjusted if needed

FAQs

How do I track costs per developer?

Portkey provides several ways to track developer costs:

• Create separate Virtual Keys for each developer
• Use metadata tags to identify developers
• Set up developer-specific API keys
• View detailed analytics in the dashboard

What happens if a developer exceeds their budget?

When a developer reaches their budget limit:

1. Further requests will be blocked
2. The developer and admin receive notifications
3. Coding history remains available
4. Admins can adjust limits as needed

Can I use Cline with local or self-hosted models?

Yes! Portkey supports local models through Ollama and other self-hosted solutions. Configure your local endpoint as a custom provider in Portkey and use it with Cline just like any other provider.

How do I ensure code security with AI assistance?

Portkey provides multiple security layers:

• Guardrails to prevent sensitive data exposure
• Request/response filtering
• Audit logs for all interactions
• Custom security rules
• PII detection and masking

Next Steps

Join our Community

• Discord Community
• GitHub Repository

Schedule a Demo

Schedule a 1:1 call with our team to see how Portkey can transform your development workflow with Cline. Get personalized recommendations for your team’s specific needs.

For enterprise support and custom features for your development teams, contact our enterprise team.