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synapse-swarm

Skill48 starsChanged 5 months agoMITView on GitHub

Multi-agent cognitive swarm with three chained AI agents — ZERO (vision analyst), NOVA (tactical strategist), and TITAN (final arbiter) — that collaboratively analyze visual input through a Streamlit dashboard. Supports voice and text commands with TTS output.

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SKILL.md

Synapse Swarm

A three-agent cognitive swarm system for real-time visual analysis using Hermes Agent.

When to Use

  • Analyzing camera or image input with multi-perspective AI reasoning
  • Running a chained agent pipeline: vision → strategy → arbitration
  • Building operator dashboards with real-time agent collaboration
  • Voice-controlled agent workflows with text-to-speech feedback
  • Tactical or creative analysis requiring multiple AI viewpoints

How It Works

Synapse Swarm chains three specialized agents in sequence:

  1. ZERO (Vision Analyst) — Receives the operator's command and a camera snapshot. Describes key visual details with tactical precision.
  2. NOVA (Tactical Strategist) — Reads ZERO's visual scan and the original command. Suggests a creative strategic angle based on the observed object or scene.
  3. TITAN (Arbiter) — Receives all prior context — the command, ZERO's scan, and NOVA's tactic — then delivers a final one-sentence verdict. TITAN's response is also spoken aloud via text-to-speech.

Each agent calls hermes chat under the hood, forming a chain-of-thought pipeline where each agent builds on the previous one's output.

Architecture

Operator Command (voice or text)
        │
        ▼
   ┌─────────┐
   │  ZERO   │  ← Camera snapshot + command
   │ (Vision)│
   └────┬────┘
        │ visual scan
        ▼
   ┌─────────┐
   │  NOVA   │  ← ZERO's scan + command
   │(Tactical)│
   └────┬────┘
        │ tactical angle
        ▼
   ┌─────────┐
   │  TITAN  │  ← All context → final verdict (+ TTS)
   │(Arbiter)│
   └─────────┘

Features

  • Chained multi-agent reasoning — Each agent receives the full context chain from previous agents
  • Customizable system prompts — Modify each agent's core directives via the sidebar
  • Dual input modes — Voice commands (auto-detected language: TR/EN) and text input
  • Text-to-speech output — TITAN's final verdict is spoken aloud automatically
  • Export reports — Download the full swarm analysis as a .txt file
  • Cyberpunk Streamlit UI — Animated GIF avatars, translucent panels, neon accents

Requirements

  • Python 3.8+
  • Hermes Agent CLI (hermes chat)
  • Streamlit
  • Pillow, SpeechRecognition, gTTS, audiorecorder
  • Camera access (for live snapshot input)

Quick Start

pip install streamlit pillow SpeechRecognition gTTS streamlit-audiorecorder
streamlit run app.py

Customization

Agent prompts can be edited in the sidebar at runtime. Each prompt supports these variables:

  • {command} — The operator's directive
  • {zero_scan} — ZERO's visual analysis output
  • {nova_tactic} — NOVA's tactical suggestion

Source

Download now (ZIP)

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