GENIUS MONOREPO // MULTI-PROGRAM

Autonomous scientific workflows across physics & engineering codes.

GENIUS orchestrates VASP, Quantum ESPRESSO, LAMMPS, SPPARKS, and GROMACS via a 6-stage AI recommendation pipeline — from natural language intent to validated simulation inputs — powered by Smart Knowledge Graphs, Hybrid Search, and Multi-LLM hierarchies.

5 Simulation Engines
1,600+ KG Parameters
6-Stage AI Pipeline
CORE ARCHITECTURE

Eight Engines of Multi-Code Intelligence

From knowledge graph parameter retrieval to finite state machine execution. Hover & drag to inspect live interactive engines.

[ENG-01] KNOWLEDGE GRAPH
APACHE AGE

Smart Knowledge Graph

Apache AGE + pgvector graph database with TXC paramjson trees, taxonomy crosswalks, and intent vocabularies across 1,600+ parameters for VASP, QE, LAMMPS, and SPPARKS.

[ENG-02] RECOMMENDATION
6-STAGE PIPELINE

AI Recommendation Pipeline

6-stage pipeline: Intent Extraction → Seed Discovery → Dependency Expansion → Value Assignment → Validation → Output Generation. OpenRouter with heuristic model routing and batch concurrency.

[ENG-03] DFT & QUANTUM
VASP + QE

DFT Input Generation

VASP INCAR generation (558 tags) with version-gating (6.4/6.5), SOC/hybrid/GW compatibility. QE pw.x inputs (240 params) with k-grid, pseudopotential, and DFT+U validation.

[ENG-04] CLASSICAL MD & MC
LAMMPS + SPPARKS

MD & Monte Carlo Engines

LAMMPS script generation (768 commands, Intel build) with EAM/Tersoff/ReaxFF/NEB support. SPPARKS input generation (101 commands) for Ising, Potts, diffusion, and AM melt-pool simulations.

[ENG-05] HYBRID SEARCH
ONNX + PGVECTOR

Hybrid Search Engine

ONNX embedding model (all-MiniLM-L12-v2) with pgvector similarity search, full-text PostgreSQL indexing, per-program search indexes, and context-aware snippet retrieval.

[ENG-06] DOCKER EXECUTION
DOCKER + SSH

Docker & HPC Execution

Containerized simulation execution via Docker (LAMMPS, QE, VASP images) or SSH+Slurm dispatch to HPC clusters. MPI topology, NEB replica partitioning, and automatic job staging.

[ENG-07] DOE & OPTIMIZATION
BAYESIAN OPT

Design of Experiments & Optimization

R-based classical DoE via Docker runtime, surrogate modeling, Bayesian optimization campaigns, and main-effects analysis for automated experiment planning.

[ENG-08] GRAPH EXPLORER
VUE 3 + EXPRESS

Graph Explorer & Wiki

Vue 3 + Vite interactive graph visualization, Express API backend, MediaWiki knowledge base with bot-driven ingestion, and taxonomy-driven parameter navigation.

RECOMMENDATION PIPELINE

6-Stage AI Recommendation Pipeline

From natural-language intent to validated simulation input files — fully automated parameter discovery, expansion, and assignment.

READY
INTENT
NL → Conditions
SEED
TXC Discovery
EXPAND
Dependency Graph
ASSIGN
LLM Values
VALIDATE
Review + Output
[SYS] GENIUS Recommendation Engine initialized.
[SYS] Loaded paramjson indexes: VASP (558), QE (240), LAMMPS (768), SPPARKS (101).
[READY] Awaiting natural-language calculation request...
SCF Energy Convergence
[API] RECOMMENDATION & SEARCH SERVICES GENIUS
FASTAPI ENDPOINTS

Declarative, multi-code,
and production-ready.

Generate validated simulation input files from plain-text calculation requests. GENIUS handles intent extraction, parameter discovery, dependency expansion, LLM assignment, and compatibility validation across all supported simulation codes.

Hybrid search API with ONNX embeddings
Apache AGE graph explorer with Vue 3 UI
Multi-program recommendation pipeline
Docker-based simulation execution
workflow_api.sh — FastAPI Server & Workflow Dispatch
# POST /workflow/ — Submit Calculation Intent to FastAPI Backend (port 8001)
curl -X POST "http://127.0.0.1:8001/workflow/" \
  -H "Content-Type: application/json" \
  -d '{
    "calculation_prompt": "Relax CeO2 with Quantum ESPRESSO & compute MD with LAMMPS",
    "lm_api": "your_openrouter_api_key",
    "gen_model_hierarchy": ["databricks/dbrx-instruct", "meta-llama/llama-3.1-405b-instruct"],
    "project_config": { "name": "CeO2_Cloud_Job", "num_retries_permodel": 3 }
  }'

# Monitor Real-Time Log Stream (Server-Sent Events)
curl -N "http://127.0.0.1:8001/logs"

# Retrieve Status & Computed Results
curl "http://127.0.0.1:8001/workflow-status/{workflow_id}"
curl "http://127.0.0.1:8001/results/{workflow_id}" | jq
OPEN SOURCE FRAMEWORK

Ready to Automate Your Scientific Workflows?

Streamline your computational research across VASP, Quantum ESPRESSO, LAMMPS, SPPARKS, and GROMACS with the GENIUS autonomous lab monorepo.