Nebulix AI Framework with split Local (Offline) and Cloud (Gist) engines.
Project description
🧬 Nebulix AI Framework (v1.0.3)
Nebulix AI is a professional, high-performance, modular AI framework developed by Nebulix Labs. It features a split architecture offering both a 100% Local (Offline) heavy knowledge engine and a Cloud (Online) fallback framework.
- License Holder: Kshitij Rajput (Founder of Nebulix Labs)
- License Type: Proprietary & Close Source
⚠️ CRITICAL DEVELOPER GUIDELINES (Read Before Integration)
1️⃣ Run Integration Tests First
Before deploying or connecting this framework to your production frontend, ensure you test all modules (local and cloud) locally using dummy sessions to verify optimal connectivity.
2️⃣ Understand the Unique Token Requirement (Strict Rule)
Do NOT attempt to use this framework without a valid authorization token, even for normal text processing or local offline actions.
- Authentication is mandatory for all modes.
- If you bypass or skip the
auth_tokenparameter during initialization, critical modules (like Robot Mode, Vision Processing, and custom responses) will be completely locked or missed. - Always enforce token passing in your production pipeline.
3️⃣ Frontend Parsing & Unique Output Patterns
The framework returns responses embedded with specialized structural markers to safely bypass large LLM dependencies. Your frontend team must analyze these unique text patterns and custom symbols to accurately render headers and code blocks:
- Headers Indicator (
****): When a response block begins or ends with****(e.g.,****Header Text****), the frontend must treat this text as a structural Header component. - Code Block Indicator (
*): Raw code segments generated by the framework (Python, HTML, React) are explicitly wrapped inside four asterisks (*) at the beginning and the end.- Example format returned by engine:
* \n [Your Generated Code Here] \n * - The frontend must capture text inside these unique markers to dynamically inject them into an Editor or a Highlight Component.
- Example format returned by engine:
🛠️ Quick Architecture Implementation
📂 Mode A: 100% Local Heavy Engine (Offline data)
Loads perfect_1.json through perfect_46.json dynamically from local storage while verifying the core developer signature online.
import asyncio
from nebulix import local # Imports the offline engine package route
async def run_offline():
# Auth token is strictly required for normal use too
ai = local(auth_token="PROPRIETARY_AUTH_TOKEN", power_level=4, ai_name="My AI")
response = await ai.chat(token="user_session_id", query="hi")
print(response["answer"])
asyncio.run(run_offline())
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