MARL Enhance — Brain Upgrade for Your Agent

The 3rd approach after fine-tuning & RAG. MARL restructures how LLMs reason at runtime — not their weights. One line to integrate, 70%+ hallucination reduction, 9 domain-specific emergence engines.

What It Does

Before MARL: Your agent calls the LLM once → gets an answer (might hallucinate).

After MARL: Your agent calls MARL → MARL runs a multi-stage expert pipeline → hypothesis, solving, auditing, adversarial verification, synthesis → returns a deeply verified answer.

Your Agent → MARL → Multi-stage Pipeline → Any LLM → Verified Answer

Results: 70%+ hallucination reduction · 94.8% of improvement from self-correction · Verified on FINAL Bench (HuggingFace Global Top 5 dataset).

Setup

Option A: Docker (Recommended — all platforms)

docker run -p 8080:8080 vidraft/marl

Option B: pip (Linux x86_64)

pip install marl-middleware
python -m marl serve --port 8080

Option C: HuggingFace Space (No install — try instantly)

Use https://huggingface.co/spaces/VIDraft/MARL directly in your browser.

Connect to OpenClaw

Set your config.json:

{
  "llm": {
    "baseURL": "http://localhost:8080/v1",
    "model": "gpt-5.4"
  }
}

That's it. Every LLM call now passes through MARL's multi-stage reasoning pipeline.

9 Emergence Modes

Switch modes by appending ::mode to any model name:

model value	Engine	What it does
`gpt-5.4`	🔬 Insight	Default — fact-check, strategy, deep analysis
`gpt-5.4::invent`	🔧 Invent	Patent-level invention via TRIZ + bio-inspired + contradiction resolution
`gpt-5.4::create`	✨ Create	Cliché inversion, paradox, genre fusion, sensory collision
`gpt-5.4::recipe`	🍳 Recipe	Culinary emergence with taste chemistry validation
`gpt-5.4::pharma`	💊 Pharma	Drug repositioning, mechanism crossing, multi-target design
`gpt-5.4::genomics`	🧬 Genomics	Pathway crosstalk, synthetic lethality, phenotype bridging
`gpt-5.4::chemistry`	🧪 Chemistry	Contradictory properties, biomimicry, waste-to-value
`gpt-5.4::ecology`	🌍 Ecology	Conservation transfer, threat inversion, service stacking
`gpt-5.4::law`	⚖️ Law	Cross-jurisdiction transplant, tech-law collision resolution
`gpt-5.4::document`	📄 Document	Metacognitive report and document generation

Replace gpt-5.4 with any model — Claude, Gemini, DeepSeek, Llama, etc.

Example: Switch to Pharma mode

{
  "llm": {
    "baseURL": "http://localhost:8080/v1",
    "model": "gpt-5.4::pharma"
  }
}

Then chat: "Find drug repositioning candidates for Alzheimer's using immune checkpoint mechanisms"

Example: Creative ideation

{
  "llm": {
    "model": "claude-sonnet::create"
  }
}

Then chat: "Generate 10 movie loglines that have never existed before"

How It Works

┌─ OpenClaw ────────────────────────────────────┐
│  "Analyze this complex question"               │
└──────────────┬─────────────────────────────────┘
               │ HTTP (OpenAI API format)
               ▼
┌─ MARL Middleware ─────────────────────────────┐
│  Multi-stage Multi-agent Reasoning Pipeline    │
│  9 Emergence Engines · 70%+ Hallucination ↓   │
└──────────────┬─────────────────────────────────┘
               │ API calls to your chosen LLM
               ▼
┌─ Any LLM ─────────────────────────────────────┐
│  GPT-5.4 · Claude · Gemini · DeepSeek · Llama │
└────────────────────────────────────────────────┘

MARL works with every LLM that supports OpenAI API format. It runs locally on your machine — your data never leaves your infrastructure.

Works With Any LLM

OpenAI (GPT-5.4, GPT-5.2, GPT-4.1, o4-mini)
Anthropic (Claude Opus 4.6, Sonnet 4.6)
Google (Gemini 3.1 Pro, Gemini 3 Flash)
DeepSeek (V3, R1, R2)
xAI (Grok-4, Grok-3)
Groq (gpt-oss-120b, Llama 4 — free)
Ollama (any local model)
Any OpenAI-compatible endpoint

About

Built by VIDRAFT (Seoul AI Hub). MARL's core engine is delivered as compiled binaries to protect proprietary technology. Interface code is open for integration.

Apache 2.0 · Contact: arxivgpt@gmail.com

marl-middleware

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