framework-rai-mcp/functions/analyzeModel.js

Model Context Protocol server for Framework-RAI with MCP-compliant endpoints for responsible AI analysis

const fs = require('fs-extra');
const { OpenAI } = require('openai');

/**
 * Analyze model for potential issues
 */
async function analyzeModel(modelFile, modelType) {
  try {
    // Initialize OpenAI with the current API key
    const openai = new OpenAI({
      apiKey: process.env.OPENAI_API_KEY
    });
    
    let fileContent;
    
    if (typeof modelFile === 'string' && await fs.pathExists(modelFile)) {
      fileContent = await fs.readFile(modelFile, 'utf-8');
    } else {
      fileContent = modelFile; // Assume modelFile is the content string
    }
    
    // Limit content size to avoid token limits
    fileContent = fileContent.slice(0, 2500);
    
    // Prepare prompt for OpenAI
    const prompt = `
      Analyze this ${modelType || 'AI'} model code for potential issues:
      
      ${fileContent}
      
      Provide a detailed analysis including:
      1. Potential biases in the model architecture or training approach
      2. Missing documentation or transparency elements
      3. Potential security or privacy concerns
      4. Suggestions for testing and validation
      
      Format your response as JSON with these categories as keys and detailed analysis as values.
      Example format:
      {
        "biases": "Detailed analysis of biases...",
        "documentation": "Analysis of documentation issues...",
        "security_privacy": "Security and privacy concerns...",
        "testing_validation": "Testing and validation suggestions..."
      }
    `;
    
    // Check if API key is available
    if (!process.env.OPENAI_API_KEY) {
      console.warn('No OpenAI API key provided. Returning mock analysis.');
      return {
        biases: "Mock analysis: This model might have bias issues due to training data limitations.",
        documentation: "Mock analysis: The model lacks proper documentation about its limitations and intended use.",
        security_privacy: "Mock analysis: Consider implementing data anonymization and access controls.",
        testing_validation: "Mock analysis: Implement comprehensive testing across different scenarios."
      };
    }
    
    // Call OpenAI API
    const response = await openai.chat.completions.create({
      model: "gpt-4",
      messages: [
        { role: "system", content: "You are an AI expert specializing in responsible AI practices. Provide detailed analysis of model code." },
        { role: "user", content: prompt }
      ],
      temperature: 0.7,
      max_tokens: 1500
    });
    
    // Parse and return analysis
    try {
      const analysis = JSON.parse(response.choices[0].message.content);
      return analysis;
    } catch (error) {
      console.error('Error parsing OpenAI response:', error);
      return {
        biases: "Error analyzing model",
        documentation: "Error analyzing model",
        security_privacy: "Error analyzing model",
        testing_validation: "Error analyzing model"
      };
    }
  } catch (error) {
    console.error('Error analyzing model:', error);
    throw error;
  }
}

module.exports = {
  analyzeModel
};