Skill: cutechicken99/marl-middleware (version 1.0.0)

--- name: marl-middleware description: Multi-stage multi-agent reasoning middleware that reduces LLM hallucination by 70%+. 9 specialized emergence engines for invention, creative, pharma, genomics, chemistry, ecology, law, recipe, and document generation. tags: [reasoning, hallucination, multi-agent, metacognition, emergence, middleware] metadata: clawdbot: config: requiredEnv: [] example: | llm: baseURL: "http://localhost:8080/v1" model: "gpt-5.4::create" --- # 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. [![PyPI](https://img.shields.io/pypi/v/marl-middleware?color=6366f1&label=PyPI)](https://pypi.org/project/marl-middleware/) [![GitHub](https://img.shields.io/badge/GitHub-Repository-24292e?logo=github)](https://github.com/Vidraft/MARL) [![Demo](https://img.shields.io/badge/🤗%20Demo-HuggingFace-ff9d00)](https://huggingface.co/spaces/VIDraft/MARL) [![FINAL Bench](https://img.shields.io/badge/🏆%20FINAL%20Bench-Global%20%235-16a34a)](https://huggingface.co/spaces/FINAL-Bench/Leaderboard) ## 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) ```bash docker run -p 8080:8080 vidraft/marl ``` ### Option B: pip (Linux x86_64) ```bash 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`: ```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 ```json { "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 ```json { "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 ## Links - **PyPI:** [pip install marl-middleware](https://pypi.org/project/marl-middleware/) - **GitHub:** [github.com/Vidraft/MARL](https://github.com/Vidraft/MARL) - **Demo:** [HuggingFace Space](https://huggingface.co/spaces/VIDraft/MARL) - **FINAL Bench:** [Leaderboard](https://huggingface.co/spaces/FINAL-Bench/Leaderboard) - **Website:** [vidraft.net](https://vidraft.net) ## 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: [REDACTED_SECRET]


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)