Documentation
Comprehensive guides, tutorials, and reference materials for implementing Prompt Folding™ in your AI applications.
Quick Start Guide
Get Started in 5 Minutes
Install the SDK
Choose your preferred language and install the Prompt Folding™ library
Configure Your API Key
Set up authentication with your preferred AI model provider
Create Your First Fold
Build and test your first hierarchical prompt structure
Optimize & Deploy
Fine-tune your prompts and deploy to production
# Install the Python SDK
pip install prompt-folding
# Basic implementation
from prompt_folding import PromptFolder
folder = PromptFolder(api_key="your-key")
# Create a simple fold
result = folder.fold({
"context": {
"system": "Expert AI assistant",
"domain": "Technical support"
},
"layers": [
{"type": "comprehension", "weight": 0.3},
{"type": "generation", "weight": 0.7}
]
})
print(result.optimized_prompt)Documentation Sections
Getting Started
Installation guides, basic setup, and your first prompt fold implementation.
Core Concepts
Understanding hierarchical composition, recursive optimization, and adaptive context management.
API Reference
Complete API documentation with examples for all endpoints and methods.
Tutorials
Step-by-step tutorials for common use cases and advanced implementations.
Best Practices
Optimization strategies, performance tips, and production deployment guidelines.
FAQ
Frequently asked questions and troubleshooting guides for common issues.
Community Forum
Connect with AI developers, share solutions, and contribute to the future of prompt engineering
Categories
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Code Examples
import prompt_folding as pf
# Initialize the folder
folder = pf.PromptFolder(
api_key="your-openai-key",
model="gpt-4"
)
# Create a complex fold
fold_config = {
"context": {
"system": "Expert AI assistant",
"domain": "Technical support",
"tone": "Professional"
},
"layers": [
{
"type": "comprehension",
"weight": 0.3,
"focus": "user_intent"
},
{
"type": "generation",
"weight": 0.7,
"focus": "response_quality"
}
],
"optimization": {
"target_tokens": 150,
"quality_threshold": 0.8
}
}
# Fold the prompt
result = folder.fold(fold_config)
print(f"Original tokens: {result.original_tokens}")
print(f"Optimized tokens: {result.optimized_tokens}")
print(f"Reduction: {result.reduction_percentage}%")
print(f"Quality score: {result.quality_score}")import { PromptFolder } from '@prompt-folding/core';
// Initialize the folder
const folder = new PromptFolder({
apiKey: 'your-openai-key',
model: 'gpt-4'
});
// Create a fold configuration
const foldConfig = {
context: {
system: 'Expert AI assistant',
domain: 'Technical support',
tone: 'Professional'
},
layers: [
{
type: 'comprehension',
weight: 0.3,
focus: 'user_intent'
},
{
type: 'generation',
weight: 0.7,
focus: 'response_quality'
}
],
optimization: {
targetTokens: 150,
qualityThreshold: 0.8
}
};
// Fold the prompt
const result = await folder.fold(foldConfig);
console.log(`Original tokens: ${result.originalTokens}`);
console.log(`Optimized tokens: ${result.optimizedTokens}`);
console.log(`Reduction: ${result.reductionPercentage}%`);
console.log(`Quality score: ${result.qualityScore}`);Ready to Get Started?
Join thousands of developers who are already using PromptFolding to optimize their AI applications.