sift-core 1.0.0

Lightweight prompt context minification engine wrapper for SiftPrompt.

sift-core

SiftPrompt Python SDK: The ultra-lightweight prompt optimization matrix compiler. Strip syntactic noise, conversational fluff, and redundancy from your LLM prompts to save up to 40%+ on your token bills without sacrificing semantic accuracy.

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Features

• Intelligent Compression: Automatically targets conversational filler, over-engineered phrasing, and corporate boilerplate.
• Fail-Safe Circuit Breaker: Zero-dependency, defensive engineering. If your network or the gateway drops, the SDK automatically fails open under 50ms, returning your raw prompt so your application never crashes.
• Multi-Mode Support: Choose between balanced, aggressive, and exact optimization matrices.
• Deterministic Local Guardrails: Instantly catches empty strings or dead whitespace locally without wasting API network credits.

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Installation

Install the official package from PyPI using pip:

pip install sift-core

Configuration

We recommend using .env.local files to manage your API keys.

1. Install the helper: pip install python-dotenv
2. Create a .env.local file in your root:

   SIFT_RAPIDAPI_KEY=your_key_here
   

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Quick Start

Python

import os
from sift_core import SiftCompiler

# Initialize the compiler with your RapidAPI key
sift = SiftCompiler(api_key="YOUR_SIFT_RAPIDAPI_KEY")

# A conversational prompt heavy with fluff
verbose_prompt = (
    "Hey there AI, I hope you are having an absolutely wonderful day today! "
    "I am working on a small personal project and I was really wondering if you could "
    "do me a huge favor. Can you please act as a world-class, expert senior copywriter "
    "for me right now? Please look over the text very carefully. Thank you so much!"
)

# Execute the compression pass
result = sift.minify(verbose_prompt, mode="aggressive")

print(f"Optimization Rate: {result.metrics['percentage_saved']}% tokens saved")
print("--------------------------------------------------")
print(f"Minified Output:\n\"{result.optimized_text}\"")

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Optimization Profiles

Profile	Behavior	Ideal Target
balanced	Standard pruning	Multi-turn conversational contexts
aggressive	High-density stripping	Verbose corporate boilerplate, pleasantries, and fluff
exact	Literal matching	Structured code blocks, JSON schemas, structural variables

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Enterprise Resilience (Fail-Open)

This SDK is engineered defensively for mission-critical pipelines, data science workflows, and autonomous AI agents.

It encapsulates network dispatches inside short-circuit timeouts.

If the underlying API layer undergoes throttling (429), structural validation denials (403), or total network blackouts, the wrapper catches the anomaly cleanly and returns your original uncompressed text sequence seamlessly with an explicit:

{
  "percentage_saved": 0
}

metric payload.

Your application's core LLM loop will never crash.