caio-atharva 1.0.10

Minify LLM prompts to reduce API token costs

CAIO (Cost-Aware Inference Orchestration)

CAIO is a high-performance optimization engine designed to drastically reduce LLM API costs. It employs a "hardcore" minification strategy that intelligently scrubs amateur conversational noise ("fluff") and compresses code-centric prompts before transmission, ensuring you only pay for the tokens that matter.

---

Key Features

• Generalized NLP Scrubber: Intelligently identifies and removes non-essential conversational text (greetings, politeness, fluff) while preserving core logic and code context.
• Code Minifier: Strips comments, unnecessary whitespace, and formatting overhead to maximize token density.
• Tiered Optimization: Flexible optimization tiers (e.g., 'dev') to suit different stages of the development lifecycle.
• Cost-Efficient: Directly reduces the token count sent to providers like OpenAI, Google Gemini, and Anthropic.

---

Installation

Install the package via pip:

pip install caio-atharva

---

Usage Example

Import CAIO, initialize it with your target model, and start optimizing your prompts immediately.

from caio import CAIO

# Initialize the optimizer. Specify your target model (default: gemini-1.5-flash)
optimizer = CAIO(model="provider-5/gemini-3-pro")

# Your original, verbose prompt
bloated_prompt = """
Hello there! I hope you are having a great day.
I'm new to Python and I was wondering if you could please help me.
Could you write a function to calculate the fibonacci sequence?
Make sure it's recursive. Thanks so much!
"""

# Optimize the prompt using the 'dev' tier for maximum efficiency
result = optimizer.optimize(bloated_prompt, tier="dev")

# Access and print the results
print(f"Original Length: {len(bloated_prompt)}")
print(f"Optimized Prompt: {result['optimized_prompt']}")
print(f"Tokens/Chars Saved: {result['tokens_saved']}")

Output

The optimized prompt sent to the LLM will look like this:

CODE-ONLY;NO-CHAT;MINIFY-RESPONSE: write a function to calculate the fibonacci sequence? Make sure it's recursive.

---

Impact Comparison

See how CAIO transforms a standard prompt into a cost-efficient payload.

Feature	Bloated Prompt (Expensive)	CAIO Optimized Prompt (Efficient)
Content	"Hi! Please write a Python script for binary search. Thanks!"	CODE-ONLY;NO-CHAT;MINIFY-RESPONSE: write a Python script for binary search.
Token Load	High (Includes social overhead)	Low (Pure instruction & code)
Cost	$$$ ( paying for "Please" and "Thanks" )	$ ( Paying only for logic )
Latency	Slower processing of extra text	Faster inference

---

Project Structure

CAIO-SDK/
├── caio/
│   ├── __init__.py
│   └── optimizer.py  # Core logic: CAIO class & NLP scrubber
├── setup.py          # Package configuration
└── README.md         # Documentation

---

Metadata

• Developer: Atharva Matale
• License: MIT License
• Version: 1.0.7
• Version: 1.0.10

---

Maximize efficient inference. Minimize costs. Use CAIO.