bleujs v1.1.2

.js/core

• Bleu.js is a Rule-based AI framework designed to provide pinpoint solutions to various problems. It's is a JavaScript framework built to tackle the various coding challenges developers face.

Features

• Advanced debugging
• Automates dependency management
• Ensure Code Quality: Tools to ensure the highest code quality
• Generate Eggs: Automatically generate code snippets
• Provides tools to maintain code quality without adding extra complexity
• Real-time optimization suggestions
• Streamlines collaboration
• Support for multiple programming languages
• Manage Dependencies: Handle project dependencies efficiently

Prerequisites

Install the bleujs package using pnpm:

pnpm add bleujs@1.1.2

bleujs start

or

pnpm install bleujs@latest

pnpm run start

Retrieve Package Information

pnpm info bleujs

Directory Structure

• core-engine: Contains the main logic for code generation, optimization, and debugging.
• language-plugins: Modules for different programming languages.
  • javascript: JavaScript-specific tools.
  • python: Python-specific tools.
• collaboration-tools: Tools for code review, issue tracking, and project management.
• dependency-management: Tools for monitoring and managing dependencies.
• code-quality-assurance: Tools for continuous code quality checks and analysis.
• eggs-generator: Tools for generating code snippets and optimization suggestions by HenFarm.js, the framework built by Helloblue.
• docker: Docker configuration files.

Features

Core Engine

• Efficient CPU core utilization through worker (Agent) processes
• Automatic worker restart for high availability
• Dynamic code generation and template management
• Enhanced logging with winston integration
• Comprehensive metrics tracking
• WebSocket connection management
• Request rate limiting
• Health monitoring
• Graceful shutdown handling

Changelog (v1.1.2)

Bleu.js v1.1.2 introduces major improvements in the AI and machine learning pipeline, focusing on XGBoost model efficiency, training, and real-time predictions. This version ensures enhanced performance, robustness, and scalability.

XGBoost Model v1.1.2

🔹 Key Updates in v1.1.2

Enhanced XGBoost Model Handling

• The model is now loaded safely with exception handling and feature validation
• Optimized error handling ensures smooth execution in production

Improved Feature Preprocessing

• Features are now auto-adjusted to match the model's expected input dimensions
• Padding logic ensures that missing features do not break predictions

Multi-threaded Predictions

• Predictions now run on separate threads, reducing blocking behavior and improving real-time inference speed

Hyperparameter Optimization with Optuna

• Uses Optuna to find the best hyperparameters dynamically
• Optimized for higher accuracy, faster predictions, and better generalization

Advanced Model Performance Metrics

• The training script now tracks Accuracy, ROC-AUC, F1 Score, Precision, and Recall
• Feature importance analysis improves explainability

Scalable Deployment Ready

• The model and scaler are saved in pkl format for easy integration
• Ready for cloud deployment and enterprise usage

📂 XGBoost Model Training Overview

The new version includes a robust training pipeline with:

• Data Scaling: Uses StandardScaler for normalization
• Hyperparameter Optimization: Finds the best combination of:
  • n_estimators
  • max_depth
  • learning_rate
  • subsample
  • colsample_bytree
  • reg_alpha
  • reg_lambda
• Final Model Performance:
  • Accuracy: 🚀 Improved for real-world datasets
  • Prediction Confidence: ✅ Higher reliability in decision-making

🔧 How to Use

1️⃣ Model Loading

Activate the Virtual Environment If you're using bash/zsh (macOS/Linux):

source ~/Bleu.js/bleujs-env/bin/activate

If you're using fish shell:

source ~/Bleu.js/bleujs-env/bin/activate.fish

If you're using Windows (cmd or PowerShell):

~/Bleu.js/bleujs-env/Scripts/activate

The model is automatically loaded at runtime with proper exception handling:

from xgboost_model import predict

input_features = [0.5, 0.3, 0.8, 1.2, 0.7, 0.9, 1.1, 0.6, 0.4, 1.0]  # Example input
result = predict(input_features)
print(result)

2️⃣ Training a New Model

To train a new XGBoost model with Optuna, run:

python train_xgboost.py

Best Accuracy: 0.9450 Best ROC-AUC: 0.9869 Best F1 Score: 0.9488 Best Precision: 0.9444 Best Recall: 0.9533

3️⃣ Deploying Bleu.js v1.1.2

The trained model can be deployed using AWS Lambda, Flask, FastAPI, or Docker.

Advanced AI Components

• Multi-head Attention Mechanisms
• LLaMA Model Integration
• Advanced NLP Processing
• Performance Optimization Suite
• Custom Transformer Architecture

Bleu.js - LLaMA Model & Backend Debugging Guide

🚀 Running & Debugging the LLaMA Model

python -m debugpy --listen 5678 --wait-for-client src/ml/models/foundation/llama.py

This allows VSCode or another debugger to attach to the running process.

Profile Model Performance (Bottleneck Analysis)

python -m torch.utils.bottleneck src/ml/models/foundation/llama.py

This provides insights into model performance bottlenecks.

Run LLaMA Model on GPU (if available)

CUDA_VISIBLE_DEVICES=0 python src/ml/models/foundation/llama.py

Forces execution on GPU for better performance.

✅ Expected Output

✅ LLaMA Attention Output Shape: torch.Size([1, 512, 4096])

📌 Profiling & Performance Analysis

🔬 cProfile Summary (Python Profiler Output)

• torch.nn.linear and torch.matmul are the heaviest operations.

• apply_rotary_embedding accounts for about 10ms per call.

🏆 Top autograd Profiler Events

`top 15 events sorted by cpu_time_total  ------------------  ------------  ------------  ------------  ------------  ------------  ------------                  Name    Self CPU %      Self CPU   CPU total %     CPU total  CPU time avg    # of Calls    ------------------  ------------  ------------  ------------  ------------  ------------  ------------        aten::uniform_        17.73%      62.645ms        17.73%      62.645ms      62.645ms             1          aten::linear         0.00%       2.918us        13.71%      48.415ms      48.415ms             1          aten::matmul         0.00%       9.332us        13.70%      48.404ms      48.404ms             1              aten::mm        13.70%      48.385ms        13.70%      48.385ms      48.385ms             1    ------------------  ------------  ------------  ------------  ------------  ------------  ------------`;

🛠️ Backend API & Testing

Run Python Tests with Pytest

pytest tests/ --disable-warnings

Install with pip install pytest if missing.

🔍 Environment Variables & .env Setup

Verify .env File Exists

cat.env;

Load .env Variables in Shell

export $(grep -v '^#' .env | xargs)   `

Verify API Key in Node.js

node -e "import 'dotenv/config'; console.log('✅ API_KEY:', process.env.API_KEY);"

Verify API Key in Python

python -c "from dotenv import load_dotenv; import os; load_dotenv(); print('✅ API_KEY:', os.getenv('API_KEY'))"

📂 Find Configuration Files

Find launch.json for VSCode Debugging

find ~/Bleu.js -name "launch.json"   `

Find all .env Files in Your Project

find ~/Bleu.js -name ".env"   `

✅ Final Check: Running Everything Smoothly

1. Make sure .env is loaded properly

2. Run AI Model tests

3. Run Backend tests

4. Monitor performance with bottleneck

python -m torch.utils.bottleneck src/ml/models/foundation/llama.py

✅ Expected Output

Running environment analysis...
Running your script with cProfile
✅ LLaMA Attention Output Shape: torch.Size([1, 512, 4096])
Running your script with the autograd profiler...
✅ LLaMA Attention Output Shape: torch.Size([1, 512, 4096])

--------------------------------------------------------------------------------
  Environment Summary
--------------------------------------------------------------------------------
PyTorch 2.6.0 DEBUG not compiled w/ CUDA
Running with Python 3.13 and

`pip3 list` truncated output:
numpy==2.2.3
torch==2.6.0
--------------------------------------------------------------------------------
  cProfile output
--------------------------------------------------------------------------------
         1858 function calls (1810 primitive calls) in 0.408 seconds

   Ordered by: internal time
   List reduced from 269 to 15 due to restriction <15>

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        4    0.209    0.052    0.209    0.052 {method 'uniform_' of 'torch._C.TensorBase' objects}
        4    0.112    0.028    0.112    0.028 {built-in method torch._C._nn.linear}
        1    0.021    0.021    0.021    0.021 {built-in method torch.randn}
        2    0.018    0.009    0.018    0.009 {built-in method torch.matmul}
        1    0.008    0.008    0.010    0.010 src/ml/models/foundation/llama.py:99(apply_rotary_embedding)
        1    0.008    0.008    0.008    0.008 {method 'softmax' of 'torch._C.TensorBase' objects}
        1    0.005    0.005    0.163    0.163 src/ml/models/foundation/llama.py:81(forward)
        3    0.004    0.001    0.004    0.001 {built-in method torch.cat}
        2    0.003    0.001    0.003    0.001 {built-in method torch.arange}
        4    0.002    0.001    0.002    0.001 {built-in method torch.empty}
        1    0.002    0.002    0.002    0.002 {method 'float' of 'torch._C.TensorBase' objects}
        1    0.002    0.002    0.002    0.002 {method 'cos' of 'torch._C.TensorBase' objects}
        1    0.001    0.001    0.001    0.001 {built-in method torch.einsum}
        1    0.001    0.001    0.003    0.003 /Users/pejmanhaghighatnia/Bleu.js/bleujs-env/lib/python3.13/site-packages/torch/_tensor.py:1075(__rdiv__)
        1    0.001    0.001    0.001    0.001 {built-in method torch.pow}

--------------------------------------------------------------------------------
  autograd profiler output (CPU mode)
--------------------------------------------------------------------------------
        top 15 events sorted by cpu_time_total

------------------  ------------  ------------  ------------  ------------  ------------  ------------
              Name    Self CPU %      Self CPU   CPU total %     CPU total  CPU time avg    # of Calls
------------------  ------------  ------------  ------------  ------------  ------------  ------------
    aten::uniform_        18.03%      46.352ms        18.03%      46.352ms      46.352ms             1
    aten::uniform_        17.99%      46.245ms        17.99%      46.245ms      46.245ms             1
    aten::uniform_        17.69%      45.479ms        17.69%      45.479ms      45.479ms             1
    aten::uniform_        17.62%      45.306ms        17.62%      45.306ms      45.306ms             1
      aten::linear         0.00%       4.875us         9.85%      25.333ms      25.333ms             1
      aten::linear         0.00%       2.125us         9.81%      25.219ms      25.219ms             1
      aten::matmul         0.00%       7.250us         9.81%      25.210ms      25.210ms             1
          aten::mm         9.80%      25.195ms         9.80%      25.195ms      25.195ms             1
      aten::matmul         0.00%       7.584us         9.74%      25.038ms      25.038ms             1
          aten::mm         9.73%      25.014ms         9.73%      25.014ms      25.014ms             1
      aten::linear         0.00%       2.957us         9.13%      23.468ms      23.468ms             1
      aten::matmul         0.00%       6.959us         9.12%      23.455ms      23.455ms             1
          aten::mm         9.12%      23.440ms         9.12%      23.440ms      23.440ms             1
      aten::linear         0.00%       2.334us         8.87%      22.814ms      22.814ms             1
      aten::matmul         0.00%       5.917us         8.87%      22.804ms      22.804ms             1
------------------  ------------  ------------  ------------  ------------  ------------  ------------
Self CPU time total: 257.072ms

AI Tools

With built-in AI services like Natural Language Processing (NLP) and decision trees, developers can quickly integrate advanced AI capabilities into their applications without starting from scratch.

🐍 Python AI Components

• NLP Engine: language-plugins/python/
• ML Models: src/backend/src/ml/models/
  • Training: train.py
  • Evaluation: evaluate.py
• Core Application: app.py

The Python components power our advanced AI and ML capabilities:

• Natural Language Processing
• Decision Tree Models
• Model Training & Evaluation
• Real-time Performance Optimization

Backend Efficiency

The package includes setup using Express.js, MongoDB, and essential middleware like helmet for security, compression for performance, and cors for handling cross-origin requests. This allows developers to set up a scalable and secure backend efficiently.

Testing and Quality Assurance

bleujs integrates testing frameworks, including Jest for unit and integration tests, and Cypress for end-to-end tests. This ensures that applications built with this package are reliable and maintain high quality standards.

Code Linting and Formatting

By including ESLint and Prettier configurations, bleujs helps developers maintain consistent coding standards and formatting, reducing errors and improving code readability.

TypeScript Support

The package supports TypeScript, allowing developers to write safer and more maintainable code with type checking.

Swagger Documentation

The package includes tools for generating Swagger API documentation, making it easier for developers to document and share their API specifications.

Continuous Integration/Continuous Deployment (CI/CD)

The package comes with a CI/CD pipeline configuration for automated testing, linting, building, and deployment. This helps teams to integrate changes continuously and deploy applications reliably.

Docker Support

With Docker integration, developers can containerize their applications for consistent deployment across different environments. This ensures that the application runs seamlessly regardless of where it is deployed.

Real-time Features

To add real-time features like live notifications and updates to their applications.

Usage

Create an instance of the BleuJS class and use its methods to manage your code:

import BleuJS from 'bleu.js';

const bleu = new BleuJS();
const newEgg = bleu.generateEgg('This is a description of the new egg.');
console.log(newEgg);
const code = 'const x = 1; console.log(x);';
const optimizedCode = bleu.optimizeCode(code);
const dependencies = ['express', 'body-parser'];
bleu.manageDependencies(dependencies);

const isQualityCode = bleu.ensureCodeQuality(code);
console.log(`Is the code quality acceptable? ${isQualityCode}`);

bleujs-utils Package (Version 1.0.1)

The bleujs-util package provides essential utility functions that are part of the Bleu.js framework. It simplifies the process of handling various coding challenges such as dependency management, code quality checks, and optimization.

Features

• Lightweight utility functions for common tasks.
• Dependency management utilities.
• Code optimization tools.

Installation

You can install the bleujs-utils package via pip

Using pip:

pip install bleujs-utils

CLI Package Information

bleujs-utils You can view the package on PyPI: bleujs-utils on PyPI

Example 1: General Utility Function

from bleujs_utils import some_utility_function

result = some_utility_function(input_data)
print(result)

Example 2: Helper Functions for AI Integration

from bleujs_utils import ai_query

response = ai_query('What is the weather today?')
print(response)

• AI Query Tools: Provides helper functions for querying AI models, managing requests, and handling responses.
• Company Search: Utilities for fuzzy searching company names, perfect for customer service applications like HelloBlue.
• Error Handling: Custom logging and debugging utilities designed to streamline development and troubleshooting.

Example 3: CLI Tool

bleujs-utils-cli --help

Here’s how you can use the bleujs-utils package in your project:

const { optimizeCode, manageDependencies } = require('bleujs-utils');

const code = 'const   x = 1;   console.log( x);';
const optimizedCode = optimizeCode(code);
console.log('Optimized Code:', optimizedCode);

const dependencies = ['express', 'body-parser'];
manageDependencies(dependencies);

Optimizing Code

The optimizeCode function cleans up and formats code for better readability and performance.

const { optimizeCode } = require('bleujs-utils');

const code = 'const   x = 1;   console.log( x);';
const optimizedCode = optimizeCode(code);
console.log(optimizedCode);

Managing Dependencies

The manageDependencies function helps you keep track of and manage your project dependencies efficiently.

const { manageDependencies } = require('bleujs-utils');

const dependencies = ['express', 'mongoose'];
manageDependencies(dependencies);

Class Documentation

'BleuJS'

The BleuJS class provides several methods to help you manage and optimize your code.

class Bleu {
  constructor() {
    this.eggs = [];
  }

  /**
   * Generates a new code egg.
   * @param {string} description - Description of the egg.
   * @param {string} type - Type of the egg (e.g., 'model', 'utility').
   * @param {object} options - Options for generating the egg.
   * @returns {object} The generated egg.
   */
  generateEgg(description, type, options) {
    const code = this.generateCode(type, options);
    const newEgg = {
      id: this.eggs.length + 1,
      description: this.generateDescription(type, options),
      type,
      code,
    };
    this.eggs.push(newEgg);
    return newEgg;
  }

  /**
   * Generates code based on type.
   * @param {string} type - Type of the code (e.g., 'model', 'utility').
   * @param {object} options - Options for generating the code.
   * @returns {string} The generated code.
   */
  generateCode(type, options) {
    switch (type) {
      case 'model':
        return this.generateModel(options.modelName, options.fields);
      case 'utility':
        return this.generateUtility(options.utilityName, options.methods);
      default:
        throw new Error(`Unknown code type: ${type}`);
    }
  }

  /**
   * Generates model code.
   * @param {string} modelName - Name of the model.
   * @param {Array} fields - Fields of the model.
   * @returns {string} The generated model code.
   */
  generateModel(modelName, fields) {
    let code = `class ${modelName} {\n`;
    fields.forEach((field) => {
      code += `  ${field.name}: ${field.type};\n`;
    });
    code += '}';
    return code;
  }

  /**
   * Generates utility code.
   * @param {string} utilityName - Name of the utility.
   * @param {Array} methods - Methods of the utility.
   * @returns {string} The generated utility code.
   */
  generateUtility(utilityName, methods) {
    let code = `class ${utilityName} {\n`;
    methods.forEach((method) => {
      code += `  ${method}() {\n`;
      code += `    // TODO: Implement ${method}\n`;
      code += '  }\n';
    });
    code += '}';
    return code;
  }

  /**
   * Generates description based on type.
   * @param {string} type - Type of the egg.
   * @param {object} options - Options for generating the description.
   * @returns {string} The generated description.
   */
  generateDescription(type, options) {
    switch (type) {
      case 'model':
        return `Model ${options.modelName} with fields ${options.fields.map((f) => f.name).join(', ')}`;
      case 'utility':
        return `Utility ${options.utilityName} with methods ${options.methods.join(', ')}`;
      default:
        throw new Error(`Unknown code type: ${type}`);
    }
  }

  /**
   * Optimizes the provided code.
   * @param {string} code - The code to optimize.
   * @returns {string} The optimized code.
   */
  optimizeCode(code) {
    return code.replace(/\s+/g, ' ').trim();
  }

  /**
   * Manages dependencies.
   * @param {Array} dependencies - List of dependencies.
   */
  manageDependencies(dependencies) {
    dependencies.forEach((dep) => {
      console.log(`Managing dependency: ${dep}`);
    });
  }

  /**
   * Ensures code quality.
   * @param {string} code - The code to check.
   * @returns {boolean} Whether the code is of high quality.
   */
  ensureCodeQuality(code) {
    return !code.includes('var');
  }
}

module.exports = Bleu;

  Bleu
    ✓ should generate a new egg (1 ms)
    ✓ should optimize code
    ✓ should manage dependencies (10 ms)
    ✓ should ensure code quality
    ✓ should generate multiple eggs
    ✓ should handle large number of eggs (3 ms)
    ✓ should handle complex optimization
    ✓ should ensure quality of complex code

Test Suites: 1 passed, 1 total
Tests:       8 passed, 8 total
Snapshots:   0 total
Time:        0.359 s, estimated 1 s
Ran all test suites.

Constructor

constructor();

Structure

class Bleu {
  constructor() {
    this.eggs = [];
  }

  generateEgg(description, type, options = {}) {
    const newEgg = {
      id: this.eggs.length + 1,
      description,
      type,
      code: this.generateCode(type, options),
    };
    this.eggs.push(newEgg);
    return newEgg;
  }

  generateCode(type, options) {
    switch (type) {
      case 'model':
        return this.generateModel(options.modelName, options.fields);
      case 'controller':
        return this.generateController(options.controllerName, options.actions);
      case 'utility':
        return this.generateUtility(options.utilityName, options.methods);
      default:
        throw new Error(`Unknown code type: ${type}`);
    }
  }

  generateModel(modelName, fields) {
    const classFields = fields
      .map((field) => `  ${field.name}: ${field.type};`)
      .join('\n');
    const classMethods = fields
      .map(
        (field) =>
          `  get${field.name.charAt(0).toUpperCase() + field.name.slice(1)}() { return this.${field.name}; }`,
      )
      .join('\n\n');
    return `
class ${modelName} {
${classFields}

  constructor(${fields.map((field) => field.name).join(', ')}) {
    ${fields.map((field) => `this.${field.name} = ${field.name};`).join('\n    ')}
  }

${classMethods}
}

module.exports = ${modelName};
    `;
  }

  generateController(controllerName, actions) {
    const actionMethods = actions
      .map(
        (action) => `
  ${action}() {
    // ${action} logic here
  }`,
      )
      .join('\n');
    return `
class ${controllerName} {
${actionMethods}
}

module.exports = ${controllerName};
    `;
  }

  generateUtility(utilityName, methods) {
    const utilityMethods = methods
      .map(
        (method) => `
  ${method.name}(${method.params.join(', ')}) {
    ${method.body}
  }`,
      )
      .join('\n');
    return `
class ${utilityName} {
${utilityMethods}
}

module.exports = ${utilityName};
    `;
  }

  optimizeCode(code) {
    const optimizedCode = code;
    return optimizedCode;
  }

  manageDependencies(dependencies) {
    dependencies.forEach((dep) => {
      console.log(`Managing dependency: ${dep}`);
    });
  }

  ensureCodeQuality(code) {
    const isQualityCode = true;
    return isQualityCode;
  }
}

module.exports = Bleu;

const Bleu = require('./Bleu');

const bleu = new Bleu();

const newEgg = bleu.generateEgg('This is a test egg', 'model', {
  modelName: 'TestModel',
  fields: [
    { name: 'field1', type: 'string' },
    { name: 'field2', type: 'number' },
  ],
});

const code = 'const x = 1;   console.log(x);';
const optimizedCode = bleu.optimizeCode(code);
console.log('Optimized Code:', optimizedCode);

const isQualityCode = bleu.ensureCodeQuality(code);
console.log('Is the code quality acceptable?', isQualityCode);

const dependencies = ['express', 'body-parser'];
bleu.manageDependencies(dependencies);

pnpm test

 PASS  tests/bleu.test.js
  API Tests
    ✓ should return Hello, World! on GET / (49 ms)
    ✓ should create data on POST /data (113 ms)
    ✓ should create multiple data entries on POST /data (114 ms)
    ✓ should handle /data with body {} (10 ms)
    ✓ should handle /nonexistent with body null (6 ms)
    ✓ should handle /data with body Invalid JSON (5 ms)
    ✓ should handle asynchronous errors gracefully (12 ms)
    ✓ should handle edge cases (4 ms)
    ✓ should ensure performance meets expectations (4 ms)
    ✓ should return 400 for missing data field in POST /data (5 ms)
    ✓ should return 500 for simulated server error in POST /data (7 ms)
    ✓ should handle invalid JSON gracefully (3 ms)
    ✓ should handle very large data payloads (106 ms)
    ✓ should measure response time for POST /data (110 ms)
    ✓ should handle simultaneous requests (148 ms)
    ✓ should validate response schema (6 ms)
    ✓ should stress test the server (263 ms)
    ✓ should test with invalid routes (5 ms)
    ✓ should test JSON parsing error (3 ms)
    ✓ should test different HTTP methods on /data (5 ms)
    ✓ should handle very large number of simultaneous requests (1235 ms)
    ✓ should handle concurrent GET and POST requests (108 ms)
    ✓ should handle slow network conditions gracefully (110 ms)
    ✓ should handle invalid request headers (10 ms)
    ✓ should verify CORS headers (7 ms)
    ✓ should handle session cookies (116 ms)
    ✓ should verify content-type for POST /data (9 ms)
    ✓ should test for memory leaks (274 ms)
    ✓ should handle different user roles (111 ms)
    ✓ should handle database connectivity issues (5 ms)
    ✓ should handle multipart/form-data (110 ms)
    ✓ should handle application/x-www-form-urlencoded (113 ms)
    ✓ should handle JSON arrays (11 ms)
    ✓ should handle deeply nested JSON objects (114 ms)

Test Suites: 1 passed, 1 total
Tests:       34 passed, 34 total
Snapshots:   0 total
Time:        3.707 s, estimated 4 s
Ran all test suites.

Initializes a new instance of the BleuJS class

Methods

Class Constructor:

The class constructor initializes the Bleu object with an empty array eggs to store the generated code 'eggs'. This array acts as a container for all the code snippets, models, utilities, and other structures created using the generateEgg method.

• Initializes an empty array eggs to store the generated code 'eggs'.

  constructor() {
  this.eggs = [];
  this.henFarm = new HenFarm();
}

generateEgg Method:

The generateEgg method is responsible for generating a new code 'egg'. This method leverages the HenFarm.js framework to produce code snippets based on the specified type and options. Each generated egg is assigned a unique ID, a description, and the generated code. The egg is then added to the eggs array and returned.

• Utilize HenFarm.js to generate code based on the provided type and options.
• Create a new egg object with a unique ID, description, type, generated code, and creation timestamp.
• Append the new egg to the eggs array.
• Return the newly created egg.

Eggs Generator API

The Eggs Generator API is a microservice that generates custom AI-powered "eggs" based on provided parameters. This API is designed for scalability, AI logic, and real-time egg generation.

If you want faster execution and better debugging, use:

curl -X POST http://localhost:3003/api/eggs/generate-egg \
     -H "Content-Type: application/json" \
     -H "Accept: application/json" \
     -H "User-Agent: Curl-Advanced-Test" \
     -H "Cache-Control: no-cache" \
     -d '{
          "type": "celestial",
          "description": "A rare legendary egg",
          "parameters": {
              "size": "large",
              "color": "gold",
              "rarity": "legendary",
              "element": "magic"
          }
        }' \
     --fail --silent --show-error --output response.json

Then, check your response.json

Expected result

{"success":true,"result":{"id":"990321c6-7cae-472f-933d-743a9ac8022c","type":"dragon","description":"A rare legendary egg","metadata":{"tags":[],"version":"1.0.37","generatedBy":"Eggs-Generator v1.0.37","properties":{"rarity":"legendary","element":"fire"},"rarity":"legendary","attributes":[{"trait_type":"element","value":"fire","rarity_score":4,"_id":"67b0a38eae7bb50b80649417"}],"dna":"1bd6e02ead46f6927bf1c5f185bfcf38","generation":1,"aiFingerprint":"9833bf1a6f857eac2fe43e0d42d8cf6b6c45382300ff0146dc396441457c536c"},"status":"incubating","incubationConfig":{"startTime":"2025-02-15T14:24:14.877Z","duration":86400,"temperature":37,"conditions":[],"optimalTemp":37},"evolution":{"stage":1,"powerLevel":104,"experience":0,"history":[],"possibleEvolutions":[]},"interactions":{"total":0,"history":[]},"owner":"system","tradeable":true,"market":{"listed":false,"bids":[],"realTimePrice":0,"priceHistory":[]},"security":{"validation":false,"signature":"233b4233de9948536c2931dfd876e2c66ad4ffe2bb46e8e9e7fca464994d1a5a"},"_id":"67b0a38eae7bb50b80649416","ownershipHistory":[],"createdAt":"2025-02-15T14:24:14.881Z","updatedAt":"2025-02-15T14:24:14.881Z","__v":0},"market":{"tier":{"eggsPerDay":5,"rarities":["common","uncommon"],"price":0},"tradingEnabled":false}}%

curl -X POST http://localhost:3003/api/eggs/generate-egg \
     -H "Content-Type: application/json" \
     -d '{
          "type": "celestial",
          "description": "A rare legendary egg",
          "parameters": { "size": "large", "color": "gold", "rarity": "legendary", "element": "magic" }
        }'

Expected result

Generated Egg: {
  id: '9854f6da-b409-4b72-bd30-7e545d79b1a7',
  type: 'golden-egg',
  description: 'A rare legendary egg',
  metadata: {
    size: 'large',
    color: 'gold',
    generatedBy: 'Eggs-Generator v1.0.37',
    timestamp: '2025-02-09T06:14:51.061Z'
  },
  createdAt: '2025-02-09T06:14:51.061Z',
  updatedAt: '2025-02-09T06:14:51.061Z'
}
2025-02-09T06:14:51.063Z [INFO]: ✅ Egg Generated Successfully {"result":{"id":"9854f6da-b409-4b72-bd30-7e545d79b1a7","type":"golden-egg","description":"A rare legendary egg","metadata":{"size":"large","color":"gold","generatedBy":"Eggs-Generator v1.0.37","timestamp":"2025-02-09T06:14:51.061Z"},"createdAt":"2025-02-09T06:14:51.061Z","updatedAt":"2025-02-09T06:14:51.061Z"}}

{
  "type": "golden-egg",
  "description": "A rare legendary egg",
  "parameters": {
    "size": "large",
    "color": "gold"
  }
}

Response (Example)

{
  "result": {
    "id": "75525d38-b458-4493-80c2-a0b01ff64c66",
    "type": "golden-egg",
    "description": "A rare legendary egg",
    "metadata": {
      "size": "large",
      "color": "gold",
      "generatedBy": "Eggs-Generator v1.0.38",
      "timestamp": "2025-02-09T01:12:03.933Z"
    },
    "createdAt": "2025-02-09T01:12:03.933Z",
    "updatedAt": "2025-02-09T01:12:03.933Z"
  }
}

 PASS  tests/bleu.test.js
  API Tests
    ✓ should return Hello, World! on GET / (49 ms)
    ✓ should create data on POST /data (113 ms)
    ✓ should create multiple data entries on POST /data (114 ms)
    ✓ should handle /data with body {} (10 ms)
    ✓ should handle /nonexistent with body null (6 ms)
    ✓ should handle /data with body Invalid JSON (5 ms)
    ✓ should handle asynchronous errors gracefully (12 ms)
    ✓ should handle edge cases (4 ms)
    ✓ should ensure performance meets expectations (4 ms)
    ✓ should return 400 for missing data field in POST /data (5 ms)
    ✓ should return 500 for simulated server error in POST /data (7 ms)
    ✓ should handle invalid JSON gracefully (3 ms)
    ✓ should handle very large data payloads (106 ms)
    ✓ should measure response time for POST /data (110 ms)
    ✓ should handle simultaneous requests (148 ms)
    ✓ should validate response schema (6 ms)
    ✓ should stress test the server (263 ms)
    ✓ should test with invalid routes (5 ms)
    ✓ should test JSON parsing error (3 ms)
    ✓ should test different HTTP methods on /data (5 ms)
    ✓ should handle very large number of simultaneous requests (1235 ms)
    ✓ should handle concurrent GET and POST requests (108 ms)
    ✓ should handle slow network conditions gracefully (110 ms)
    ✓ should handle invalid request headers (10 ms)
    ✓ should verify CORS headers (7 ms)
    ✓ should handle session cookies (116 ms)
    ✓ should verify content-type for POST /data (9 ms)
    ✓ should test for memory leaks (274 ms)
    ✓ should handle different user roles (111 ms)
    ✓ should handle database connectivity issues (5 ms)
    ✓ should handle multipart/form-data (110 ms)
    ✓ should handle application/x-www-form-urlencoded (113 ms)
    ✓ should handle JSON arrays (11 ms)
    ✓ should handle deeply nested JSON objects (114 ms)

Test Suites: 1 passed, 1 total
Tests:       34 passed, 34 total
Snapshots:   0 total
Time:        3.707 s, estimated 4 s
Ran all test suites.

pnpm test

> bleujs@1.1.2 test /Users/Bleu.js
> jest --detectOpenHandles --forceExit

 PASS   lint  coverage/prettify.js
  ✓ ESLint (66 ms)

 PASS   lint  coverage/lcov-report/prettify.js
  ✓ ESLint (29 ms)

 PASS   lint  dependency-management/coverage/prettify.js
  ✓ ESLint (30 ms)

 PASS   lint  dependency-management/coverage/lcov-report/prettify.js
  ✓ ESLint (105 ms)

 PASS   lint  venv/lib/python3.13/site-packages/werkzeug/debug/shared/debugger.js
  ✓ ESLint (12 ms)

 PASS   lint  eggs-generator/src/types/egg.types.js
  ✓ ESLint (6 ms)

 PASS   lint  backend/src/src/controllers/apiController.js
  ✓ ESLint (6 ms)

 PASS   lint  eggs-generator/src/routes/egg.routes.js
  ✓ ESLint (11 ms)

 PASS   lint  coverage/lcov-report/sorter.js
  ✓ ESLint (8 ms)

 PASS   lint  coverage/sorter.js
  ✓ ESLint (4 ms)

 PASS   lint  dependency-management/coverage/sorter.js
  ✓ ESLint (4 ms)

 PASS   lint  dependency-management/coverage/lcov-report/sorter.js
  ✓ ESLint (3 ms)

 PASS   lint  backend/src/src/ai/decisionTree.js
  ✓ ESLint (6 ms)

 PASS   lint  frontend/src/index.js
  ✓ ESLint (3 ms)

 PASS   lint  frontend/public/app.js
  ✓ ESLint (4 ms)

 PASS   lint  ./jest.setup.js
  ✓ ESLint (7 ms)

 PASS   lint  eggs-generator/src/services/egg.service.js
  ✓ ESLint (4 ms)

 PASS   lint  eggs-generator/src/events/eggEvents.js
  ✓ ESLint (6 ms)

 PASS   lint  src/backend/src/controllers/apiController.js
  ✓ ESLint (5 ms)

 PASS   lint  eggs-generator/src/Bleu.js
  ✓ ESLint (2 ms)

 PASS   lint  backend/src/src/controllers/rulesController.js
  ✓ ESLint (3 ms)

 PASS   lint  backend/src/tests/CustomSequencer.js
  ✓ ESLint (2 ms)

 PASS   lint  src/backend/routes.js
  ✓ ESLint (6 ms)

 PASS   lint  src/backend/src/ai/decisionTree.js
  ✓ ESLint (3 ms)

 PASS   lint  eggs-generator/src/models/egg.model.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/tests/apiGenerateEgg.test.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/models/ruleModel.js
  ✓ ESLint (2 ms)

 PASS   lint  src/backend/tests/CustomSequencer.js
  ✓ ESLint (2 ms)

 PASS   lint  src/backend/tests/apiController.test.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/services/aiService.js
  ✓ ESLint (3 ms)

 PASS   lint  src/backend/tests/decisionTree.test.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/controllers/dataController.js
  ✓ ESLint (1 ms)

 PASS   lint  ./manualConnectionTest.js
  ✓ ESLint (2 ms)

 PASS   lint  src/backend/src/services/aiService.js
  ✓ ESLint (1 ms)

 PASS   lint  coverage/lcov-report/block-navigation.js
  ✓ ESLint (1 ms)

 PASS   lint  coverage/block-navigation.js
  ✓ ESLint (3 ms)

 PASS   lint  dependency-management/coverage/lcov-report/block-navigation.js
  ✓ ESLint (2 ms)

 PASS   lint  dependency-management/coverage/block-navigation.js
  ✓ ESLint (4 ms)

 PASS   lint  src/backend/tests/testUtils.js
  ✓ ESLint (2 ms)

 PASS   lint  backend/src/src/ai/nlpProcessor.js
  ✓ ESLint (1 ms)

 PASS   lint  eggs-generator/__tests__/index.test.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/routes/apiRoutes.js
  ✓ ESLint (2 ms)

 PASS   lint  src/backend/tests/testSequencer.test.js
  ✓ ESLint (2 ms)

 PASS   lint  src/backend/src/ai/nlpProcessor.js
  ✓ ESLint (2 ms)

 PASS   lint  dependency-management/src/index.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/ml/modelManager.js
  ✓ ESLint (2 ms)

 PASS   lint  backend/src/src/services/rulesEngine.js
  ✓ ESLint (3 ms)

 PASS   lint  dependency-management/test.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/services/ruleService.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/src/ml/modelManager.js
  ✓ ESLint (1 ms)

 PASS   lint  src/models/egg.schema.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/src/controllers/dataController.js
  ✓ ESLint (2 ms)

 PASS   lint  src/controllers/eggController.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/tests/seedDatabase.test.js
  ✓ ESLint (2 ms)

 PASS   lint  src/backend/tests/aiService.test.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/mocks/AiQuery.js
  ✓ ESLint (2 ms)

 PASS   lint  src/backend/src/services/rulesEngine.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/tests/apiRoutes.test.js
  ✓ ESLint (3 ms)

 PASS   lint  backend/src/html-report/jest-html-reporters-attach/report/index.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/utils/testSequencer.js
  ✓ ESLint (2 ms)

 PASS   lint  language-plugins/javascript/src/index.js
  ✓ ESLint (1 ms)

 PASS   lint  eggs-generator/src/generateEgg.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/html-report/jest-html-reporters-attach/report/index.js
  ✓ ESLint

 PASS   lint  backend/src/src/routes/dataRoutes.js
  ✓ ESLint (1 ms)

 PASS   lint  eggs-generator/src/db/mongodb.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/services/decisionTreeService.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/models/userModel.js
  ✓ ESLint (1 ms)

 PASS   lint  src/middleware/security.js
  ✓ ESLint (1 ms)

 PASS   lint  eggs-generator/src/utils/metrics.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/mocks/database.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/models/AiQuery.js
  ✓ ESLint

 PASS   lint  src/middleware/auth.js
  ✓ ESLint

 PASS   lint  language-plugins/javascript/tests/index.test.js
  ✓ ESLint (2 ms)

 PASS   lint  src/backend/src/utils/testSequencer.js
  ✓ ESLint (1 ms)

 PASS   lint  dependency-management/src/dependencyManager.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/tests/aiTests.test.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/src/routes/dataRoutes.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/services/seedDatabase.js
  ✓ ESLint (1 ms)

 PASS   lint  eggs-generator/src/HenFarm.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/utils/logger.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/mocks/AiQuery.js
  ✓ ESLint (1 ms)

 PASS   lint  language-plugins/javascript/src/JSProcessor.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/tests/globalTeardown.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/tests/globalSetup.js
  ✓ ESLint (1 ms)

 PASS   lint  src/routes/eggs.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/routes/index.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/src/models/userModel.js
  ✓ ESLint (1 ms)

 PASS   lint  eggs-generator/__mocks__/HenFarm.js
  ✓ ESLint (1 ms)

 PASS   lint  eggs-generator/deploy/deploy.js
  ✓ ESLint

 PASS   lint  src/backend/tests/bleu.test.js
  ✓ ESLint

 PASS   lint  eggs-generator/src/middleware/errorHandler.js
  ✓ ESLint

 PASS   lint  src/backend/swagger.js
  ✓ ESLint (3 ms)

 PASS   lint  src/backend/src/services/seedDatabase.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/src/models/AiQuery.js
  ✓ ESLint

 PASS   lint  backend/src/src/routes/simpleRoute.js
  ✓ ESLint (2 ms)

 PASS   lint  eggs-generator/test-db.js
  ✓ ESLint (1 ms)

 PASS   lint  ./generateRuleId.js
  ✓ ESLint (2 ms)

 PASS   lint  eggs-generator/src/middleware/validation.js
  ✓ ESLint (1 ms)

 PASS   lint  eggs-generator/ecosystem.config.js
  ✓ ESLint (1 ms)

 PASS   lint  ./vite.config.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/tests/globalTeardown.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/src/utils/logger.js
  ✓ ESLint (1 ms)

 PASS   lint  code-quality-assurance/tests/index.test.js
  ✓ ESLint (2 ms)

 PASS   lint  src/backend/tests/globalSetup.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/src/services/mockEngine.js
  ✓ ESLint (1 ms)

 PASS   lint  scripts/preinstall.js
  ✓ ESLint (2 ms)

 PASS   lint  ./preinstall.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/tests/setup.js
  ✓ ESLint

 PASS   lint  src/backend/src/utils/lib/Bleu.js
  ✓ ESLint

 PASS   lint  backend/ecosystem.config.js
  ✓ ESLint (1 ms)

 PASS   lint  backend/src/tests/setupTests.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/tests/setupTests.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/src/services/mockEngine.js
  ✓ ESLint (1 ms)

 PASS   lint  ./jestSequencer.js
  ✓ ESLint (1 ms)

 PASS   lint  code-quality-assurance/src/index.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/src/routes/simpleRoute.js
  ✓ ESLint (1 ms)

 PASS   lint  src/backend/src/routes/index.js
  ✓ ESLint (2 ms)

 PASS   lint  ./eslint.config.js
  ✓ ESLint (1 ms)

 PASS   lint  eggs-generator/src/utils/asyncHandler.js
  ✓ ESLint (1 ms)

 PASS   lint  dependency-management/jest.setup.js
  ✓ ESLint (4 ms)

 PASS   lint  src/backend/src/routes/metricsRoutes.js
  ✓ ESLint (2 ms)

 PASS   lint  src/backend/src/routes/healthRoutes.js
  ✓ ESLint (1 ms)

 PASS   lint  eggs-generator/src/validators/egg.validator.js
  ✓ ESLint (1 ms)

 PASS   lint  eggs-generator/src/middleware/metrics.js
  ✓ ESLint (1 ms)

 PASS   lint  eggs-generator/asyncHandler.js
  ✓ ESLint (1 ms)

-------------------|---------|----------|---------|---------|-------------------
File               | % Stmts | % Branch | % Funcs | % Lines | Uncovered Line #s
-------------------|---------|----------|---------|---------|-------------------
All files          |       0 |        0 |       0 |       0 |
 dist              |       0 |        0 |       0 |       0 |
  routes.js        |       0 |        0 |       0 |       0 | 5-914
  swagger.js       |       0 |      100 |     100 |       0 | 4-23
 dist/utils        |       0 |        0 |       0 |       0 |
  logger.js        |       0 |      100 |       0 |       0 | 5-10
  testSequencer.js |       0 |        0 |       0 |       0 | 5-725
 dist/utils/lib    |       0 |        0 |       0 |       0 |
  Bleu.js          |       0 |        0 |       0 |       0 | 5-78
-------------------|---------|----------|---------|---------|-------------------
Test Suites: 6 skipped, 170 passed, 170 of 176 total
Tests:       216 passed, 216 total
Snapshots:   0 total
Time:        3.419 s, estimated 6 s
Ran all test suites in 2 projects.
📦 report is created on: /Users/pejmanhaghighatnia/Bleu.js/reports/test-report.html
**  jest-stare --reporters: wrote output report to ./reports/jest-stare/index.html      **

optimizeCode Method:

The optimizeCode method is designed to optimize the provided code. While currently a placeholder, this method will implement advanced code optimization techniques to enhance performance and efficiency.

• Placeholder for code optimization logic.
• Returns the optimized code.

optimizeCode(code) {

  const optimizedCode = code.replace(/\s+/g, ' ').trim();
  return optimizedCode;
}

ensureCodeQuality Method:

The ensureCodeQuality method will ensure that the provided code meets predefined quality standards. This placeholder will incorporate code analysis tools and techniques to validate the code's quality.

• Placeholder for code quality assurance logic.
• Returns a boolean indicating whether the code meets quality standards.

ensureCodeQuality(code) {

  const isQualityCode = true;
  return isQualityCode;
}

This document provides detailed information about the API endpoints available in the Bleu.js application, including the recent updates and improvements made to the API.

(On Linux, use xdg-open index.html, or open it manually on Windows.)

Test Report Overview

Here’s a snapshot of the latest test suite execution for the Bleu.js framework. Our commitment to quality ensures a robust and reliable experience for developers.

Summary

Execution Details

Detailed Execution

Bleu.js ensures all test cases pass successfully, delivering a seamless experience for developers. Below are key highlights from the executed suite:

🏗️ Top-Level Files

Backend Highlights

Core Engine Highlights

Swagger Documentation:

 * @swagger
 * /debug:
 *   post:
 *     summary: Debug logic
 *     tags: [Debug]
 *     responses:
 *       200:
 *         description: Debugging
 *         content:
 *           application/json:
 *             schema:
 *               type: string
 *               example: Debugging
 */
router.post('/debug', (req, res) => {
  res.send('Debugging');
});

POST /optimize

Handles optimization logic.

• URL: /optimize
• Method: POST
• Response:

`"Optimizing"`;

Swagger Documentation:

/**
 * @swagger
 * /optimize:
 *   post:
 *     summary: Optimize logic
 *     tags: [Optimization]
 *     responses:
 *       200:
 *         description: Optimizing
 *         content:
 *           application/json:
 *             schema:
 *               type: string
 *               example: Optimizing
 */
router.post('/optimize', (req, res) => {
  res.send('Optimizing');
});

POST /generate

Handles generation logic.

• URL: /generate
• Method: POST
• Response:

`"Generating"`;

Swagger Documentation:

/**
 * @swagger
 * /generate:
 *   post:
 *     summary: Generate logic
 *     tags: [Generation]
 *     responses:
 *       200:
 *         description: Generating
 *         content:
 *           application/json:
 *             schema:
 *               type: string
 *               example: Generating
 */
router.post('/generate', (req, res) => {
  res.send('Generating');
});

API Documentation

The API documentation is available at http://localhost:3003/docs and provides detailed information about all available endpoints, request parameters, and response structures.

Here is an example of how Swagger documentation is added for an endpoint in the backend/server.js file:

/**
 * @swagger
 * /:
 *   get:
 *     summary: Returns a greeting message
 *     responses:
 *       200:
 *         description: A JSON object containing a greeting message
 *         content:
 *           application/json:
 *             schema:
 *               type: object
 *               properties:
 *                 message:
 *                   type: string
 *                   example: Hello, World!
 */
app.get('/', (req, res) => {
  res.status(200).json({ message: 'Hello, World!' });
});

Security

The API supports bearer token authentication for secure endpoints. The security schema is defined as follows:

const swaggerDefinition = {
  openapi: '3.0.0',
  info: {
    title: 'Bleu.js API',
    version: '1.0.0',
    description: 'Documentation for the Bleu.js API',
  },
  servers: [
    {
      url: 'http://localhost:3003',
    },
  ],
  components: {
    securitySchemes: {
      bearerAuth: {
        type: 'http',
        scheme: 'bearer',
        bearerFormat: 'JWT',
      },
    },
  },
  security: [
    {
      bearerAuth: [],
    },
  ],
};

License

Bleu.js is licensed under the MIT License

This software is maintained by Helloblue, Inc., a company dedicated to advanced innovations in AI solutions.

Author

Pejman Haghighatnia