AI-Powered JavaScript Framework
Optimized for Speed
& Scalability
Built for the Future
Bleu.js is an AI-first JavaScript framework that empowers developers to build intelligent applications with unprecedented speed and efficiency.
import { createBleu } from 'bleujs'; const app = createBleu({ mode: 'streaming', optimizations: 'auto'}); app.generate('Hello, Bleu.js!') .then(result => { console.log(result); });
Why Choose Bleu.js?
The next-generation JavaScript framework designed for speed, AI-powered enhancements, and developer ease.
Lightning Fast Performance
Experience unmatched speed with Bleu.js, built for efficiency and optimized rendering.
Developer-Friendly API
Bleu.js provides an intuitive and clean API, making development smoother and more enjoyable.
AI-Powered Enhancements
Leverage AI-driven optimizations to enhance performance, debugging, and code suggestions.
Smart Asset Optimization
AI-powered optimization of images, scripts, and other assets for optimal loading performance.
Real-time Performance Monitoring
Advanced monitoring tools that provide real-time insights into your application's performance and health.
Intelligent Error Handling
AI-driven error detection and recovery system that helps prevent and resolve issues before they impact users.
Intelligent AI Components
Experience the future of AI with our cutting-edge components designed to enhance your development workflow
Core AI Capabilities
Our AI components provide powerful capabilities for modern applications:
Natural Language Processing
- Advanced text understanding and generation
- Real-time language translation and analysis
- Sentiment analysis and intent recognition
Code Intelligence
- Smart code completion and suggestions
- Automated code optimization
- Intelligent bug detection and fixes
Performance Optimization
- Dynamic resource allocation
- Automated performance tuning
- Smart caching strategies
Live AI Metrics
Real-time monitoring of AI components and neural network performance:
Implementation Guide
Python Integration
Seamlessly integrate Python with Bleu.js for enhanced development capabilities and AI-powered features.
Installation & Setup
Get started with Bleu.js Python integration in seconds
# Install the package
pip install bleujs
# Import the main utilities
from bleujs_utils import ai_query, BleuClient
# Initialize the client
client = BleuClient(api_key="your_api_key")
# Test the connection
response = client.ping()
print(f"Status: {response.status}")
AI-Powered Features
Leverage advanced AI capabilities with simple Python calls
from bleujs_utils import ai_query, code_analyzer
# AI-powered code analysis
code_sample = '''
def fibonacci(n):
if n <= 1:
return n
return fibonacci(n-1) + fibonacci(n-2)
'''
# Analyze code quality
analysis = code_analyzer.analyze(code_sample)
print(f"Quality Score: {analysis.score}")
print(f"Suggestions: {analysis.suggestions}")
# AI-powered query
response = ai_query("Optimize this fibonacci function")
print(response.answer)
Advanced Integration
Build sophisticated applications with our comprehensive API
from bleujs_utils import (
BleuClient,
ModelManager,
PerformanceMonitor
)
# Initialize components
client = BleuClient(api_key="your_api_key")
models = ModelManager(client)
monitor = PerformanceMonitor()
# Load and use AI models
model = models.load("code-optimizer")
result = model.optimize(code_input)
# Monitor performance
with monitor.track("optimization"):
optimized_code = model.process(code_input)
print(f"Processing time: {monitor.get_metrics()}")
Live Integration Metrics
Real-time monitoring of Python integration with Bleu.js v1.1.6:
Next Steps
Run Tests
Execute the test suite to verify the functionality of the application.
python -m pytest tests/
Running the Application
Start the core engine to run the application in development mode.
python main.py
Testing the API
Use these commands to test the API endpoints and verify integration.
python test_api.py
XGBoost Model Training
Bleu.js includes a robust machine learning pipeline with XGBoost integration for high-performance model training and deployment.
XGBoost Training Pipeline
Our advanced training pipeline includes comprehensive features for optimal model performance:
Data Preprocessing
- Automated feature scaling and normalization
- Missing value handling with advanced imputation
- Feature selection and importance analysis
Model Training
- Hyperparameter optimization with Optuna
- Cross-validation with stratified sampling
- Early stopping and model checkpointing
Performance Monitoring
- Real-time training metrics visualization
- Resource usage tracking and optimization
- Model performance benchmarking
Implementation Guide
1. Environment Setup
Activate the Virtual Environment and install dependencies:
2. Model Training
Train a new XGBoost model with custom parameters:
3. Model Inference
Use the trained model for predictions:
4. Deployment Options
Live Training Metrics
Real-time monitoring of XGBoost model training with Bleu.js v1.1.6:
LLaMA Model Integration
Harness the power of state-of-the-art language models with Bleu.js's seamless LLaMA integration for advanced AI capabilities.
Core Capabilities
Our LLaMA integration provides powerful features for advanced language processing:
Model Features
- 70B parameter model with optimized inference
- Multi-turn conversation support
- Context-aware responses
Performance Optimization
- Quantized model variants for efficiency
- Dynamic batching and caching
- GPU acceleration support
Advanced Features
- Fine-tuning capabilities
- Custom prompt engineering
- Multi-modal input support
Implementation Guide
1. Model Setup
Initialize the LLaMA model with Bleu.js:
2. Basic Usage
Generate text with the LLaMA model:
3. Advanced Features
Utilize advanced LLaMA capabilities:
4. Deployment Options
Live Performance Monitoring
Real-time metrics and performance data for LLaMA model with Bleu.js v1.1.6:
Code Generation
Transform your ideas into production-ready code with Bleu.js's advanced AI-powered code generation capabilities.
Core Capabilities
Our code generation engine provides powerful features for modern development:
Code Synthesis
- Full-stack application generation
- API endpoint creation
- Database schema design
Code Optimization
- Performance improvements
- Security best practices
- Code refactoring
Advanced Features
- Multi-language support
- Framework integration
- Custom templates
Implementation Guide
1. Basic Generation
Generate code from natural language descriptions:
2. Advanced Generation
Generate complete applications with multiple components:
3. Code Optimization
Optimize existing code for better performance: