RooCode Configuration

RooCode is a powerful standalone AI coding assistant application with an interactive chat interface, code review capabilities, and multi-file editing. Configure it to use MegaLLM for access to multiple AI models.

Quick Configuration

Via Application Settings
Via Configuration File
Import Configuration

Step-by-Step Setup

Open RooCode Settings

Launch RooCode application
Click the gear icon ⚙️ (bottom-left corner)
Navigate to: Settings → API Configuration

Select Provider Type

Provider Type: Select OpenAI Compatible
This enables custom base URL configuration
Allows MegaLLM integration

Configure API Endpoint

Base URL: https://ai.megallm.io/v1
API Key: sk-mega-your-api-key-here
Organization: Leave empty (not required)
Click Save

Choose Default Model

Default Model: gpt-5
Fallback Model: gpt-4o (optional)
Temperature: 0.7 (balanced creativity)
Max Tokens: 4096

Enable Features

Code Completion
Chat Interface
Code Review
Refactoring Assistant
Multi-File Edit

Scenario Examples

Scenario 1: First-Time Installation

Complete setup from downloading to first use:

Download and Install RooCode

Visit RooCode.io (example URL)
Download for your OS (Windows/macOS/Linux)
Install the application
Launch RooCode

Get MegaLLM API Key

Visit MegaLLM Dashboard
Sign up or log in
Navigate to API Keys section
Click Create New Key
Copy the key (starts with sk-mega-)

Configure API Provider

In RooCode:

Click ⚙️ Settings icon
Go to API Configuration
Select Provider: OpenAI Compatible
Enter Base URL: https://ai.megallm.io/v1
Paste API Key: sk-mega-your-key
Click Test Connection (should show ✓ Success)
Click Save

Choose Your First Model

In Settings → Model Selection
Select: gpt-5 (recommended for general use)
Or browse available models
Set Temperature: 0.7 (balanced)
Save settings

Test Configuration

Open a new chat in RooCode
Type: Hello! What model are you using?
Should respond with model information
Try: Write a hello world function in Python

Expected Response:

def hello_world():
    print("Hello, World!")

if __name__ == "__main__":
    hello_world()

Scenario 2: Team Setup with Shared Configuration

Set up RooCode for an entire development team: Scenario: Development team of 10 people need consistent RooCode configuration Step 1: Team Lead Creates Base Config team-roocode-config.json:

{
  "provider": "openai-compatible",
  "api": {
    "baseURL": "https://ai.megallm.io/v1",
    "apiKey": "TEAM_MEMBER_REPLACES_THIS",
    "model": "gpt-5",
    "temperature": 0.7,
    "maxTokens": 4096
  },
  "features": {
    "codeCompletion": true,
    "chatInterface": true,
    "codeReview": true,
    "refactoring": true,
    "multiFileEdit": true
  },
  "projectSettings": {
    "language": "typescript",
    "framework": "react",
    "codingStyle": "airbnb",
    "testFramework": "jest"
  },
  "customPrompts": {
    "review": "Review this code following our team's Airbnb style guide and best practices",
    "test": "Generate Jest unit tests with at least 80% coverage",
    "doc": "Generate JSDoc comments for this function",
    "refactor": "Refactor this code for better maintainability and TypeScript strict mode"
  },
  "ui": {
    "theme": "dark",
    "showInlineHints": true,
    "autoSaveChats": true,
    "fontSize": 14
  }
}

Step 2: Create Setup Instructions ROOCODE_SETUP.md:

# RooCode Team Setup Guide

## Prerequisites
- RooCode application installed ([Download](https://roocode.io))
- MegaLLM API key ([Get yours](https://megallm.io/dashboard))

## Setup Steps

### 1. Get Your Personal API Key
1. Go to https://megallm.io/dashboard
2. Navigate to **API Keys**
3. Click **Create New Key**
4. Copy your key (starts with `sk-mega-`)

### 2. Import Team Configuration
1. Download `team-roocode-config.json` from this repo
2. Open RooCode
3. Go to: `File → Import Configuration`
4. Select `team-roocode-config.json`

### 3. Add Your Personal API Key
1. After import, go to: `Settings → API Configuration`
2. Replace `TEAM_MEMBER_REPLACES_THIS` with your actual key
3. Click **Test Connection** (should show ✓ Success)
4. Click **Save**

### 4. Restart RooCode
Close and reopen RooCode to apply all settings.

## Verification
1. Open a new chat
2. Type: `Generate a React component for a login form`
3. Should generate TypeScript code following Airbnb style

## Troubleshooting
- **Connection failed**: Check API key is correct
- **Wrong code style**: Verify configuration imported correctly
- **Model errors**: Ensure using `gpt-5` or other supported models

## Support
Contact team lead or check [MegaLLM Docs](https://docs.megallm.io)

Step 3: Distribute to Team

# Team lead commits to repo
git add team-roocode-config.json ROOCODE_SETUP.md
git commit -m "Add RooCode team configuration"
git push

# Team members clone and setup
git pull
# Follow instructions in ROOCODE_SETUP.md

Result: Entire team uses consistent:

Same AI model (gpt-5)
Same temperature and settings
Same custom prompts
Same coding standards
Personal API keys (not shared)

Scenario 3: Project-Specific Configurations

Use different RooCode configurations for different project types: Python Data Science Project: roocode-datascience.json:

{
  "provider": "openai-compatible",
  "api": {
    "baseURL": "https://ai.megallm.io/v1",
    "apiKey": "${env:MEGALLM_API_KEY}",
    "model": "claude-opus-4-1-20250805",
    "temperature": 0.5
  },
  "projectSettings": {
    "language": "python",
    "libraries": ["numpy", "pandas", "scikit-learn", "matplotlib"],
    "codingStyle": "pep8"
  },
  "customPrompts": {
    "analyze": "Analyze this data processing code for efficiency and correctness",
    "optimize": "Optimize this pandas operation for large datasets",
    "visualize": "Suggest matplotlib visualization for this data",
    "doc": "Generate numpy-style docstring"
  }
}

React Web Application: roocode-webapp.json:

{
  "provider": "openai-compatible",
  "api": {
    "baseURL": "https://ai.megallm.io/v1",
    "apiKey": "${env:MEGALLM_API_KEY}",
    "model": "gpt-5",
    "temperature": 0.7
  },
  "projectSettings": {
    "language": "typescript",
    "framework": "react",
    "stateManagement": "zustand",
    "styling": "tailwind"
  },
  "customPrompts": {
    "component": "Generate a React functional component with TypeScript and Tailwind",
    "test": "Write React Testing Library tests for this component",
    "hook": "Create a custom React hook for this functionality",
    "api": "Generate API integration with tanstack-query"
  }
}

Systems Programming (Rust): roocode-systems.json:

{
  "provider": "openai-compatible",
  "api": {
    "baseURL": "https://ai.megallm.io/v1",
    "apiKey": "${env:MEGALLM_API_KEY}",
    "model": "gemini-2.5-pro",
    "temperature": 0.3
  },
  "projectSettings": {
    "language": "rust",
    "codingStyle": "rust-fmt"
  },
  "customPrompts": {
    "review": "Review this Rust code for memory safety and performance",
    "optimize": "Suggest optimizations for this performance-critical code",
    "test": "Generate comprehensive Rust tests",
    "unsafe": "Analyze this unsafe block for correctness"
  }
}

Switching Between Projects:

# Create aliases in ~/.bashrc or ~/.zshrc
alias roocode-ds='cp ~/configs/roocode-datascience.json ~/.config/RooCode/config.json && roocode'
alias roocode-web='cp ~/configs/roocode-webapp.json ~/.config/RooCode/config.json && roocode'
alias roocode-sys='cp ~/configs/roocode-systems.json ~/.config/RooCode/config.json && roocode'

Scenario 4: Migration from Cursor/Other AI Tools

Switching from another AI coding tool to RooCode with MegaLLM: Current Setup: Using Cursor with OpenAI Why Switch to RooCode + MegaLLM:

Access to multiple models (GPT, Claude, Gemini) with one key
Standalone app (not tied to specific editor)
Better pricing and no seat limits
More customization options

Migration Steps:

Export Current Preferences

From Cursor (if possible):

Note your preferred models
Save any custom prompts
Document keyboard shortcuts you use

Install RooCode

Download and install RooCode for your OS

Configure MegaLLM

{
  "provider": "openai-compatible",
  "api": {
    "baseURL": "https://ai.megallm.io/v1",
    "apiKey": "sk-mega-your-megallm-key",
    "model": "gpt-5"
  }
}

Recreate Custom Prompts

Add your frequently used prompts:

{
  "customPrompts": {
    "explain": "Explain this code in detail",
    "fix": "Find and fix bugs in this code",
    "improve": "Suggest improvements for this code"
  }
}

Test Functionality

Compare side-by-side:

Open same code in both tools
Ask same questions
Compare code generation quality
Evaluate response speed

Comparison Table:

Feature	Cursor	RooCode + MegaLLM
Editor Integration	VS Code fork	Standalone + Any Editor
Models Available	GPT-4, GPT-3.5	GPT, Claude, Gemini, and more
API Key	OpenAI only	One key for all models
Pricing	Per-seat subscription	Pay-per-use
Customization	Limited	Extensive
Offline Mode	No	No

Scenario 5: Multi-Model Workflow

Use different models for different types of tasks: Configuration with Model Profiles:

{
  "provider": "openai-compatible",
  "api": {
    "baseURL": "https://ai.megallm.io/v1",
    "apiKey": "sk-mega-your-api-key-here",
    "model": "gpt-5"
  },
  "modelProfiles": {
    "fast": {
      "model": "gpt-4o-mini",
      "temperature": 0.5,
      "maxTokens": 1000,
      "description": "Fast completions for simple tasks"
    },
    "balanced": {
      "model": "gpt-5",
      "temperature": 0.7,
      "maxTokens": 4096,
      "description": "Balanced quality and speed"
    },
    "quality": {
      "model": "claude-opus-4-1-20250805",
      "temperature": 0.3,
      "maxTokens": 8192,
      "description": "Highest quality for complex tasks"
    },
    "creative": {
      "model": "gpt-5",
      "temperature": 0.9,
      "maxTokens": 4096,
      "description": "Creative documentation and naming"
    },
    "analysis": {
      "model": "claude-sonnet-4",
      "temperature": 0.4,
      "maxTokens": 6000,
      "description": "Code review and analysis"
    }
  }
}

Workflow Example:

Morning: Rapid Prototyping
→ Switch to "fast" profile (gpt-4o-mini)
→ Quick code generation
→ Fast iterations

Afternoon: Production Code
→ Switch to "quality" profile (claude-opus-4)
→ Generate production-ready code
→ Comprehensive error handling

Code Review Time
→ Switch to "analysis" profile (claude-sonnet-4)
→ Detailed code reviews
→ Security analysis

Documentation
→ Switch to "creative" profile (gpt-5, high temp)
→ Generate engaging docs
→ Creative naming suggestions

Switching Profiles in RooCode:

Click model dropdown (top bar)
Select profile: Fast / Balanced / Quality / Creative / Analysis
Profile applied to current session

Scenario 6: CI/CD Integration

Use RooCode API for automated code reviews in CI/CD: GitHub Actions Example: .github/workflows/roocode-review.yml:

name: AI Code Review with RooCode

on:
  pull_request:
    types: [opened, synchronize]

jobs:
  ai-review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3

      - name: Setup RooCode CLI
        run: |
          curl -O https://roocode.io/cli/install.sh
          bash install.sh

      - name: Configure MegaLLM
        env:
          MEGALLM_API_KEY: ${{ secrets.MEGALLM_API_KEY }}
        run: |
          mkdir -p ~/.config/RooCode
          cat > ~/.config/RooCode/config.json << EOF
          {
            "provider": "openai-compatible",
            "api": {
              "baseURL": "https://ai.megallm.io/v1",
              "apiKey": "$MEGALLM_API_KEY",
              "model": "claude-sonnet-4"
            }
          }
          EOF

      - name: Run AI Code Review
        run: |
          roocode review \
            --files "$(git diff --name-only origin/main...HEAD)" \
            --output review.md

      - name: Post Review Comment
        uses: actions/github-script@v6
        with:
          script: |
            const fs = require('fs');
            const review = fs.readFileSync('review.md', 'utf8');
            github.rest.issues.createComment({
              issue_number: context.issue.number,
              owner: context.repo.owner,
              repo: context.repo.repo,
              body: `## AI Code Review\n\n${review}`
            });

Configuration Options

Complete Reference

{
  // API Configuration
  "provider": "openai-compatible",
  "api": {
    "baseURL": "https://ai.megallm.io/v1",
    "apiKey": "sk-mega-your-api-key-here",
    "organization": "",
    "model": "gpt-5",
    "temperature": 0.7,
    "maxTokens": 4096,
    "topP": 0.9,
    "frequencyPenalty": 0.0,
    "presencePenalty": 0.0,
    "timeout": 30000
  },

  // Feature Toggles
  "features": {
    "codeCompletion": true,
    "chatInterface": true,
    "codeReview": true,
    "refactoring": true,
    "multiFileEdit": true,
    "contextAwareness": true,
    "autoSave": true
  },

  // Project Settings
  "projectSettings": {
    "language": "typescript",
    "framework": "react",
    "codingStyle": "airbnb",
    "testFramework": "jest",
    "linter": "eslint"
  },

  // Custom Prompts
  "customPrompts": {
    "review": "Review code for bugs and best practices",
    "test": "Generate comprehensive unit tests",
    "doc": "Generate detailed documentation",
    "refactor": "Refactor for better maintainability",
    "optimize": "Optimize for performance",
    "secure": "Analyze for security vulnerabilities"
  },

  // UI Preferences
  "ui": {
    "theme": "dark",
    "fontSize": 14,
    "fontFamily": "Fira Code",
    "showInlineHints": true,
    "showLineNumbers": true,
    "autoSaveChats": true,
    "chatPosition": "right",
    "enableAnimations": true
  },

  // Keyboard Shortcuts
  "shortcuts": {
    "newChat": "Cmd+N",
    "sendMessage": "Cmd+Enter",
    "clearChat": "Cmd+K",
    "switchModel": "Cmd+M",
    "openSettings": "Cmd+,"
  },

  // Advanced
  "advanced": {
    "logLevel": "info",
    "cacheResponses": true,
    "maxChatHistory": 100,
    "contextWindowSize": 8000,
    "streamResponses": true
  }
}

Model Selection Guide

Task	Recommended Model	Why
Quick Completions	`gpt-4o-mini`	Fastest, cost-effective
Code Review	`claude-sonnet-4`	Excellent analysis
Complex Logic	`claude-opus-4-1-20250805`	Superior reasoning
Web Development	`gpt-5`	Best for JS/TS/React
Documentation	`gpt-5`	Clear, engaging writing
Data Science	`claude-sonnet-4`	Strong with pandas/numpy
Systems Code	`gemini-2.5-pro`	Precise, mathematical

Verification

Test 1: Chat Functionality

Open RooCode
Click New Chat
Type: Write a function to sort an array of objects by a property
Should receive working code

Expected Response:

function sortByProperty(array, property) {
  return array.sort((a, b) => {
    if (a[property] < b[property]) return -1;
    if (a[property] > b[property]) return 1;
    return 0;
  });
}

Test 2: Code Review

Paste this code:

def divide(a, b):
    return a / b

Click Review Code button
Should identify: Missing zero division check

Test 3: Multi-File Edit

Open multi-file view
Request: “Add error handling to all API calls”
Should show changes across multiple files
Review and apply changes

Test 4: Connection Status

Check status indicator (top-right):

🟢 Green = Connected to MegaLLM
🟡 Yellow = Connecting…
🔴 Red = Connection failed

Click status to see:

Model: gpt-5
Endpoint: https://ai.megallm.io/v1
Token usage: Current session stats

Troubleshooting

Connection timeout errors

Symptoms:

“Failed to connect to API”
Requests timeout after 30s
Chat messages don’t send

Solutions:

Verify base URL is correct:

https://ai.megallm.io/v1  <Icon icon="check" /> Correct
https://ai.megallm.io     <Icon icon="xmark" /> Missing /v1
https://api.openai.com/v1 <Icon icon="xmark" /> Wrong endpoint

Test connectivity:

# Test connection
curl -I https://ai.megallm.io/v1/models

# Should return: HTTP/2 200

Check firewall:
- Allow RooCode through firewall
- Check corporate proxy settings
- Verify no VPN blocking

Increase timeout:

{
  "api": {
    "timeout": 60000  // Increase to 60 seconds
  }
}

Test API key manually:

curl -X POST https://ai.megallm.io/v1/chat/completions \
  -H "Authorization: Bearer $MEGALLM_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"gpt-4o-mini","messages":[{"role":"user","content":"test"}]}'

API key not recognized

Symptoms:

“Invalid API key” error
401 Unauthorized
Authentication failed

Solutions:

Verify key format:
- Must start with sk-mega-
- Should be 60+ characters
- No extra spaces or line breaks
- No quotes in config file around the actual key
Check key is active:
- Login to Dashboard
- Go to API Keys
- Verify key shows as “Active”
- Check it’s not revoked or expired
Re-enter the key:
- Copy key from dashboard
- Delete old key from RooCode settings
- Paste new key
- Save and restart RooCode

Test key directly:

curl -H "Authorization: Bearer sk-mega-your-actual-key" \
     https://ai.megallm.io/v1/models

# Should return JSON list of models

Poor quality responses

Symptoms:

Irrelevant code suggestions
Wrong programming language
Incomplete responses

Solutions:

Provide better context:
- Set project language in settings
- Add framework information
- Use custom prompts

Adjust temperature:

{
  "api": {
    "temperature": 0.3  // Lower = more focused (0.2-0.4 for code)
  }
}

Try different model:

{
  "api": {
    "model": "claude-sonnet-4"  // Better for analysis
  }
}

Increase max tokens:

{
  "api": {
    "maxTokens": 8192  // Longer, more complete responses
  }
}

Use specific prompts:

{
  "customPrompts": {
    "generate": "Generate production-ready TypeScript code following best practices"
  }
}

Configuration not loading

Symptoms:

Settings revert after restart
Changes don’t apply
Using default configuration

Solutions:

Check config file location:

# Should be:
C:\Users\YourName\AppData\Roaming\RooCode\config.json

# Not:
C:\Program Files\RooCode\config.json  # Wrong!

Validate JSON syntax:

# Check for errors
cat config.json | python3 -m json.tool

# Should show formatted JSON or error

Check file permissions:

# Linux/macOS
chmod 644 ~/.config/RooCode/config.json

# Windows: Ensure user has read/write access

Reset to defaults:
- Backup current config
- Delete config.json
- Restart RooCode (creates new config)
- Reapply settings via UI

Application crashes or freezes

Symptoms:

RooCode crashes on startup
Freezes during long responses
Unresponsive UI

Solutions:

Check system resources:
- Close other applications
- Ensure 4GB+ RAM available
- Check CPU usage

Reduce max tokens:

{
  "api": {
    "maxTokens": 2048  // Reduce from 8192
  }
}

Disable streaming:

{
  "advanced": {
    "streamResponses": false
  }
}

Clear cache:

# Windows
rmdir /s "%APPDATA%\RooCode\cache"

# macOS/Linux
rm -rf ~/Library/Application\ Support/RooCode/cache
rm -rf ~/.config/RooCode/cache

Reinstall RooCode:
- Backup config.json
- Uninstall RooCode
- Download latest version
- Install and restore config

Best Practices

Project Configurations

Create separate configs for different project types

Model Profiles

Set up profiles for different tasks: fast, quality, creative

Custom Prompts

Define reusable prompts for common tasks

Monitor Usage

Check Dashboard regularly for token usage

Backup Configs

Keep backups of working configurations

Security

Use environment variables for API keys in shared configs

Advanced Tips

Environment Variables

RooCode supports environment variable substitution:

{
  "api": {
    "apiKey": "${env:MEGALLM_API_KEY}",
    "baseURL": "${env:MEGALLM_BASE_URL}"
  }
}

Set variables:

export MEGALLM_API_KEY="sk-mega-your-key"
export MEGALLM_BASE_URL="https://ai.megallm.io/v1"

Context Management

Improve responses with better context:

{
  "advanced": {
    "contextWindowSize": 16000,
    "includeProjectStructure": true,
    "includeOpenFiles": true,
    "maxRelevantFiles": 10
  }
}

Response Caching

Save API costs with intelligent caching:

{
  "advanced": {
    "cacheResponses": true,
    "cacheExpiry": 3600,  // seconds
    "maxCacheSize": 100   // MB
  }
}

Next Steps

Kilocode Setup

Configure Kilocode VSCode extension

Cline Setup

Configure Cline VSCode extension

Models Catalog

Browse all available models

Other Agents

View all CLI and GUI agents

API Reference

Explore the API docs

Discord Community

Join for support

Overview

Configuration

​Quick Configuration

​Step-by-Step Setup

​Scenario Examples

​Scenario 1: First-Time Installation

​Scenario 2: Team Setup with Shared Configuration

​Scenario 3: Project-Specific Configurations

​Scenario 4: Migration from Cursor/Other AI Tools

​Scenario 5: Multi-Model Workflow

​Scenario 6: CI/CD Integration

​Configuration Options

​Complete Reference

​Model Selection Guide

​Verification

​Test 1: Chat Functionality

​Test 2: Code Review

​Test 3: Multi-File Edit

​Test 4: Connection Status

​Troubleshooting

​Best Practices

Project Configurations

Model Profiles

Custom Prompts

Monitor Usage

Backup Configs

Security

​Advanced Tips

​Environment Variables

​Context Management

​Response Caching

​Next Steps

Kilocode Setup

Cline Setup

Models Catalog

Other Agents

API Reference

Discord Community

Quick Configuration

Step-by-Step Setup

Scenario Examples

Scenario 1: First-Time Installation

Scenario 2: Team Setup with Shared Configuration

Scenario 3: Project-Specific Configurations

Scenario 4: Migration from Cursor/Other AI Tools

Scenario 5: Multi-Model Workflow

Scenario 6: CI/CD Integration

Configuration Options

Complete Reference

Model Selection Guide

Verification

Test 1: Chat Functionality

Test 2: Code Review

Test 3: Multi-File Edit

Test 4: Connection Status

Troubleshooting

Best Practices

Advanced Tips

Environment Variables

Context Management

Response Caching

Next Steps