Model Marketplace

The Model Marketplace is CoAI.Dev's centralized hub for discovering, configuring, and managing AI models. It provides an intuitive interface for exploring available models, understanding their capabilities, and organizing your workspace for optimal productivity.

Overview

The marketplace serves two main functions:

1. Discovery: Browse and learn about available AI models from your configured channels
2. Workspace Management: Organize and customize which models appear in your chat interface

Marketplace Features

🎯 Model Discovery

Browse models with rich information:

• Model Cards: Visual cards with names, descriptions, and capabilities
• Category Filtering: Filter by model type (text, image, audio, code)
• Provider Grouping: Organize by AI service provider
• Capability Tags: Quick identification of model features
• Performance Metrics: Response time, cost, and availability data

📊 Model Information

Each model provides comprehensive details:

• Description: What the model does and its strengths
• Use Cases: Recommended applications and scenarios
• Parameters: Context length, max tokens, supported features
• Pricing: Token costs and rate limits
• Examples: Sample inputs and outputs
• Documentation: Links to provider documentation

🏷️ Smart Categorization

Models are automatically categorized by:

Workspace Management

Adding Models to Workspace

Workspace Organization

Organize your models for efficient access:

📋 My Workspace
├── 🎯 Primary Models
│   ├── GPT-4 (Complex tasks)
│   ├── Claude (Writing & analysis)
│   └── Gemini Pro (Multimodal)
├── ⚡ Quick Tasks
│   ├── GPT-3.5 Turbo (Fast chat)
│   └── Code Llama (Programming)
└── 🎨 Creative
    ├── DALL-E 3 (Images)
    └── Midjourney (Art)

Model Configuration

Each workspace model can be customized:

{
  "model_id": "gpt-4",
  "display_name": "GPT-4 Pro",
  "description": "For complex analysis and reasoning",
  "custom_parameters": {
    "temperature": 0.7,
    "max_tokens": 4096,
    "system_prompt": "You are a helpful assistant..."
  },
  "tags": ["analysis", "writing", "reasoning"],
  "enabled": true,
  "show_in_workspace": true
}

Model Categories and Use Cases

Text Generation Models

Specialized Models

Advanced Features

Custom Model Integration

Add private or custom models:

{
  "name": "Custom Model",
  "type": "openai",
  "base_url": "https://your-model-api.com/v1",
  "api_key": "your-api-key"
}

{
  "id": "custom-model-v1",
  "name": "My Custom Model",
  "description": "Specialized model for specific tasks",
  "capabilities": ["text-generation", "custom-domain"],
  "context_length": 4096,
  "pricing": {
    "input_tokens": 0.001,
    "output_tokens": 0.002
  }
}

Model Templates

Create reusable model configurations:

{
  "template_name": "Code Review Assistant",
  "base_model": "gpt-4",
  "system_prompt": "You are an expert code reviewer...",
  "parameters": {
    "temperature": 0.3,
    "max_tokens": 2048
  },
  "suggested_use_cases": [
    "Code review",
    "Bug detection", 
    "Optimization suggestions"
  ]
}

A/B Testing

Compare model performance:

Best Practices

Workspace Organization

• Categorize by Purpose: Group models by use case rather than provider
• Limit Active Models: Keep workspace focused with 5-10 frequently used models
• Use Descriptive Names: Add context to model names for quick identification
• Regular Cleanup: Remove unused models to maintain organization

Model Selection

• Match Task Complexity: Use appropriate model power for the task
• Consider Cost: Balance performance needs with budget constraints
• Test Performance: Evaluate models with your specific use cases
• Monitor Usage: Track which models provide the best value

Performance Optimization

• Cache Common Responses: Enable caching for frequently asked questions
• Batch Similar Requests: Group related queries for efficiency
• Optimize Prompts: Craft prompts that work well with specific models
• Monitor Metrics: Track response times and success rates

Troubleshooting

Model Not Appearing

Performance Issues

Slow Responses:

• Check channel health and response times
• Consider using faster models for simple tasks
• Verify network connectivity to model providers
• Review prompt complexity and length

High Costs:

• Monitor token usage patterns
• Use appropriate models for task complexity
• Implement caching for repeated queries
• Set usage quotas and alerts

Configuration Problems

Model Won't Add to Workspace:

1. Verify you have permission to access the model
2. Check for workspace limits or quotas
3. Ensure model is properly configured in channels
4. Review any error messages in logs

Integration Examples

Custom Workspace Setup

// Example: Setting up a development-focused workspace
const devWorkspace = {
  models: [
    {
      id: "gpt-4",
      name: "Code Architect",
      prompt: "You are a senior software architect...",
      tags: ["architecture", "design"]
    },
    {
      id: "code-llama",
      name: "Code Assistant", 
      prompt: "You are a coding assistant...",
      tags: ["coding", "debugging"]
    },
    {
      id: "gpt-3.5-turbo",
      name: "Quick Helper",
      prompt: "You are a helpful assistant...",
      tags: ["general", "quick"]
    }
  ]
};

Automated Model Selection

# Example: Dynamic model selection based on task type
def select_model(task_type, complexity):
    if task_type == "code" and complexity == "high":
        return "gpt-4"
    elif task_type == "code" and complexity == "low":
        return "code-llama"
    elif task_type == "general":
        return "gpt-3.5-turbo"
    else:
        return "claude-3"

Ready to explore models? Navigate to the model marketplace in your CoAI.Dev admin panel to discover available models, or check out Channel Management to add more AI providers to your instance.