| --- |
| license: mit |
| title: HELIOS Space Weather Intelligence |
| sdk: static |
| emoji: 🌖 |
| colorFrom: yellow |
| colorTo: yellow |
| pinned: true |
| thumbnail: >- |
| https://cdn-uploads.huggingface.co/production/uploads/67b98fe3225257ced68e868f/GyAano-lheu4xu90cIKBc.png |
| short_description: First multi-agent AI system for real-time solar storm detect |
| --- |
| # HELIOS — Real-Time Space Weather Intelligence |
|
|
| > First multi-agent AI system for real-time solar storm detection and infrastructure impact forecasting. |
| > Running NASA/IBM Surya-1.0 on AMD Instinct MI300X via ROCm. |
|
|
| **AMD Developer Hackathon · May 4–10, 2026 · lablab.ai** |
|
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| --- |
|
|
| ## Demo |
|
|
| 🎥 |
| https://www.loom.com/share/a15bf3391c0945e7950ff213460d3ced |
| [](https://www.loom.com/share/a15bf3391c0945e7950ff213460d3ced) |
| Live dashboard: `http://134.199.197.132` *(active during hackathon)* |
|
|
| --- |
|
|
| ## What It Does |
|
|
| HELIOS watches the Sun 24/7, detects solar storms as they form, models how they travel through space, and delivers plain-language impact forecasts to operators — telling them exactly which satellites, power grids, GPS systems, and aviation routes face risk, and when. |
|
|
| **The problem:** When a CME arrives at Earth, the DSCOVR sensor at the L1 Lagrange point gives operators approximately 30 minutes of real-time warning — verified at 31 minutes for the May 2024 Gannon G5 storm. That is not enough time to complete protective actions for critical infrastructure. |
|
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| **HELIOS detects flares at the solar source** using GOES X-ray data and NASA's Surya foundation model, issuing automated WARNING alerts days before Earth impact — rather than waiting for the storm to arrive at DSCOVR's L1 position. For the Gannon storm, our pipeline issued a WARNING 36 hours before impact, validated against real NASA DONKI and GFZ Potsdam archives. |
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| --- |
|
|
| ## Architecture |
|
|
| ``` |
| ┌─────────────────────────────────────────────────────────┐ |
| │ LIVE DATA SOURCES │ |
| │ NASA SDO (images) │ NOAA DSCOVR │ GOES X-ray │ |
| └──────────┬──────────┴───────┬────────┴──────┬───────────┘ |
| │ │ │ |
| ▼ ▼ │ |
| ┌─────────────────┐ ┌─────────────────┐ │ |
| │ AGENT 01 │ │ AGENT 02 │◄──┘ |
| │ Solar Vision │ │ CME Physics │ |
| │ Surya-1.0 │ │ DSCOVR L1 │ |
| │ GOES X-ray │ │ Burton / DBM │ |
| └────────┬────────┘ └────────┬────────┘ |
| │ (parallel) │ |
| └────────┬───────────┘ |
| ▼ |
| ┌─────────────────┐ |
| │ AGENT 03 │ |
| │ Impact Mapper │ |
| │ Kp → Infra │ |
| │ Folium map │ |
| └────────┬────────┘ |
| ▼ |
| ┌─────────────────┐ |
| │ AGENT 04 │ |
| │ Command LLM │ |
| │ Llama 3.1 8B │ |
| │ Alert bulletin │ |
| └────────┬────────┘ |
| ▼ |
| ┌─────────────────┐ |
| │ OPERATOR DASH │ |
| │ Streamlit UI │ |
| │ Live + Replay │ |
| └─────────────────┘ |
| ``` |
|
|
| Agents 01 and 02 run in **true parallel** via `ThreadPoolExecutor` — GOES/SDO fetch and DSCOVR fetch are independent. They sync at Agent 03. |
|
|
| --- |
|
|
| ## Benchmark — Surya-1.0 on AMD MI300X |
|
|
| | Metric | Value | |
| |---|---| |
| | Surya VRAM (weights + activation) | **1.82 GB** | |
| | GOES X-ray live signal latency | **~170 ms** | |
| | All models loaded simultaneously | **~145 GB total** | |
| | MI300X total VRAM | **192 GB** | |
| | Full pipeline latency (no storm) | **< 1 second** | |
| | Full pipeline latency (alert path) | **~30 seconds** (includes LLM) | |
|
|
| **Why MI300X:** |
| Llama 3.1 8B (~16 GB fp16) + Surya (~1.82 GB) + vLLM overhead — all loaded simultaneously in one VRAM pool. No model swapping. The MI300X's 5.2 TB/s memory bandwidth enables real-time inference within SDO's 12-second image cadence. |
|
|
| --- |
|
|
| ## Tech Stack |
|
|
| | Layer | Tool | Version | |
| |---|---|---| |
| | GPU | AMD Instinct MI300X | 192 GB VRAM | |
| | GPU Runtime | ROCm | 7.2 | |
| | Solar Model | NASA/IBM Surya-1.0 (HelioSpectFormer) | 366M params | |
| | LLM | Llama 3.1 8B (vLLM) | 0.17.1 | |
| | Agent Framework | LangGraph | latest | |
| | Solar Physics | DSCOVR + Burton empirical formula | — | |
| | Geo Mapping | Folium | latest | |
| | Dashboard | Streamlit | latest | |
|
|
| **Models used in this submission:** Surya-1.0 (366M) + Llama 3.1 8B Instruct via vLLM on AMD ROCm 7.2. |
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| --- |
|
|
| ## Data Sources |
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| All data is **free, public, and streaming in real time**: |
|
|
| | Source | What | URL | |
| |---|---|---| |
| | NASA SDO | Live solar images (AIA 171Å) | `sdo.gsfc.nasa.gov` | |
| | NOAA DSCOVR mag | Bz magnetic field (nT) | `services.swpc.noaa.gov` | |
| | NOAA DSCOVR plasma | Solar wind speed (km/s) | `services.swpc.noaa.gov` | |
| | NOAA GOES | X-ray flux (flare class) | `services.swpc.noaa.gov` | |
| | NOAA SWPC | Kp index | `services.swpc.noaa.gov` | |
| | SuryaBench | Historical storm data (.nc) | `github.com/NASA-IMPACT/SuryaBench` | |
|
|
| --- |
|
|
| ## Agent Specifications |
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| | Agent | Model | Input | Output | |
| |---|---|---|---| |
| | 01 Solar Vision | Surya-1.0 + GOES X-ray | SDO image sequence / GOES flux | Flare probability, severity | |
| | 02 CME Physics | Burton formula + DBM | DSCOVR Bz + plasma speed | Kp estimate, storm class | |
| | 03 Impact Mapper | Lookup table + Folium | Kp index | Geo risk map, per-sector impacts | |
| | 04 Command LLM | Llama 3.1 8B via vLLM | All agent outputs | Plain-language alert bulletin | |
|
|
| --- |
|
|
| ## Quickstart |
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| **Fresh AMD Developer Cloud instance — complete setup in one command per step:** |
|
|
| ```bash |
| # On the AMD host (run once): |
| bash <(curl -s https://raw.githubusercontent.com/hadsaw-parallel/helios/main/setup_host.sh) |
| |
| # Inside the Docker container: |
| docker exec -it rocm /bin/bash |
| cd /app && git clone https://github.com/hadsaw-parallel/helios.git && cd helios && bash setup.sh |
| ``` |
|
|
| `setup.sh` automatically: |
| 1. Clones the repo and installs dependencies |
| 2. Clones NASA-IMPACT/Surya and installs it |
| 3. Downloads Surya-1.0 weights from HuggingFace |
| 4. Starts vLLM serving Llama 3.1 8B |
| 5. Starts Streamlit dashboard on port 30000 |
| 6. Proxied to port 80 via Caddy |
|
|
| **Dashboard opens at `http://<YOUR_IP>`** (~15 min from zero on a fresh instance). |
|
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| --- |
|
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| ## Running Tests |
|
|
| ```bash |
| python3 -m pytest tests/ -v |
| # 9 passed, 1 skipped (storm replay requires SuryaBench data) |
| ``` |
|
|
| --- |
|
|
| ## What Makes HELIOS Unique |
|
|
| 1. **First demonstration of NASA/IBM Surya-1.0 on AMD ROCm hardware.** Surya's GitHub targets CUDA only. HELIOS ports and runs it on MI300X — a direct AMD ecosystem contribution. |
|
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| 2. **First multi-agent agentic pipeline for operational space weather forecasting.** Existing tools are siloed: separate apps for solar imaging, solar wind data, and impact assessment. HELIOS chains them into one autonomous pipeline. |
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| 3. **Scientifically grounded physics.** Agent 02 uses real DSCOVR measurements (not synthetic data) and the Burton (1975) empirical formula for Kp estimation. Agent 03's latitude bands match NOAA's published G-scale. |
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| 4. **Validated against real storms.** The counterfactual replay fetches live data from NASA DONKI, GFZ Potsdam Kp API, and NASA OMNIWeb for any historical timestamp — nothing hardcoded. Validated against the May 2024 Gannon G5 storm: HELIOS issued WARNING at T-36h using real archived flare data. The live pipeline shows real conditions (ALL_CLEAR when the Sun is quiet). |
| |
| --- |
| |
| ## The Warning Window |
| |
| | Detection mode | Lead time | Source | |
| |---|---|---| |
| | DSCOVR at L1 real-time solar wind | **~30 minutes** | Verified: 31 min for Gannon storm (NOAA SWPC) | |
| | NOAA analyst watch (CME + coronagraph) | ~2 days | Manual human process, not automated | |
| | **HELIOS automated WARNING (flare detection)** | **Hours to days** | Validated: T-36h for Gannon using NASA DONKI archives | |
| |
| HELIOS detects X-class flares at the solar source using GOES X-ray — the same data NOAA analysts use, but in an automated pipeline that also maps infrastructure impact and generates operator bulletins in under 3 seconds. DSCOVR provides the final real-time confirmation as the storm arrives; HELIOS provides the early automated alert before it does. |
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| --- |
| |
| ## Validated Claim |
| |
| *"The May 2024 Gannon G5 storm — strongest in 21 years. DSCOVR gave operators 31 minutes of real-time warning when the CME was already arriving. HELIOS, running the same public GOES data through an automated pipeline, issued a WARNING 36 hours before impact — validated live against NASA DONKI and GFZ Potsdam archives."* |
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| --- |
| |
| *Built with NASA/IBM Surya-1.0 · AMD Instinct MI300X · ROCm 7.2 · LangGraph · Llama 3.1* |
| *AMD Developer Hackathon · May 4–10, 2026* |
