fluxstate-edge 1.0.0

Zero-Trace Contextual Edge Video Analytics SDK

FluxState: Edge Intelligence SDK

FluxState is an enterprise-grade, Zero-Trace Edge Video Analytics SDK. It operates as a camera-agnostic intelligence overlay (Intelligent Video Recorder model), designed to ingest RTSP streams from legacy IP cameras and apply advanced, multi-modal behavioral reasoning.

Unlike legacy systems that rely on facial recognition or hardcoded rules, FluxState utilizes a Behavioral Threat Matrix—fusing kinetic movement, acoustic escalation, and RF network device tracking into a singular Reality Graph.

🚀 Core Enterprise Features

• Zero-Trace Privacy Engine: Compliant with strict GDPR and Defense data-retention policies. Pixel buffers are processed entirely in ephemeral RAM and cryptographically overwritten (zeroed out) instantly post-inference, preventing memory-dump attacks.
• RTSP IP Camera Integration: Connects seamlessly to existing infrastructure. No proprietary hardware required.
• Webhooks Integration Bus: Operates purely headlessly. Emits near-instant JSON telemetry payloads to centralized Video Management Systems (VMS) or command center dashboards via POST webhooks only when threats are detected.
• Over-The-Air (OTA) Policy Engine: Threat definitions and thresholds are defined in intelligence_policy.json, allowing central command to push dynamic parameter updates to fleet edge nodes without restarting the stream.
• Multi-Modal Swarm Tracking (GPASS): Tracks anonymous geometric identities across frames. Uses YOLOv8 (Vision), Mediapipe (Skeletal Kinetics), PyAudio (Acoustic Impact), and ARP Scanning (RF Device Payloads) to generate a unified threat vector.

📦 Installation & Setup

1. System Dependencies: Ensure Tesseract OCR and network tools are installed.

   brew install tesseract
   

2. Install the SDK: You can build and install this SDK directly via pip:

   pip install -e .
   

🛠️ Seamless Developer Integration

FluxState is designed as a Headless B2B SDK. It is the intelligence layer ("The Brain") that you embed into your own proprietary backend or UI.

Create a Python script (e.g., example_integration.py):

import time
from app import FluxStateNode

# 1. Initialize the SDK (Zero-Trace Mode Enabled by Default)
sdk = FluxStateNode()

# 2. Define your seamless integration hooks
def handle_threat(event_payload):
    print(f"\n[🚨 INTEGRATION BUS] Threat Detected! Escalating to VMS...")
    print(f"Target: {event_payload['entities']}")
    print(f"Vector: {event_payload['context_log']}")

# 3. Bind hooks to the SDK
sdk.on_threat_detected = handle_threat

# 4. Deploy Headlessly (Runs entirely in background RAM, no UI)
sdk.start_headless_daemon()

try:
    while True: time.sleep(1)
except KeyboardInterrupt:
    print("Shutting down SDK...")

🔐 Publishing to PyPI (Trusted Publisher)

This repository is configured for highly secure OIDC Trusted Publishing to PyPI via GitHub Actions. There is no need for manual API tokens or twine.

1. Go to the PyPI Pending Publishers page.
2. Enter the following exact details to link your repository:
   • PyPI Project Name: fluxstate-edge
   • Owner: IAMVINAY (or your GitHub username)
   • Repository name: fluxstate
   • Workflow name: publish.yml
   • Environment name: pypi
3. Click "Add".
4. On GitHub, create a new Release. The included .github/workflows/publish.yml will automatically build the SDK wheel and securely publish it to PyPI!