README.md

metadata

title: SuperAI Forecast
emoji: 📈
colorFrom: blue
colorTo: cyan
sdk: docker
app_port: 7860
pinned: false

SuperAI Forecast

SuperAI Forecast is a FastAPI + Lightweight Charts application for live market analysis with a multi-model AI forecast stack: Kronos, Google TimesFM, and Amazon Chronos.

Core Features

• multi-source OHLCV data with automatic fallback
• technical indicator calculation
• independent Kronos / TimesFM / Chronos forecasting
• unified OHLC4 forecast contract across all AI models
• real-time WebSocket price streaming
• single-origin frontend served directly from the backend

Runtime Requirements

• Windows with Python 3.11
• Internet access for market data
• Internet access on the first TimesFM model load if the checkpoint is not cached locally

Quick Start

run.bat

The launcher validates the virtual environment, ensures the local AI model dependencies are ready, applies the TimesFM compatibility patch, starts the backend, and opens the dashboard automatically.

Manual Start

py -3.11 -m venv venv
venv\Scripts\python.exe -m pip install -r requirements.txt
venv\Scripts\python.exe -m backend.launcher

Project Layout

SuperAI Forecast/
|-- backend/
|   |-- main.py
|   |-- frontend_assets.py
|   |-- launcher.py
|   |-- server_runtime.py
|   |-- forecasting/
|   `-- startup_utils.py
|-- frontend/
|   |-- app.js
|   |-- forecast-models.js
|   |-- index.html
|   |-- workspace.js
|   `-- workspace.css
|-- libs/
|   `-- chronos-forecasting/
|-- scripts/
|   `-- patch_timesfm.py
|-- requirements.txt
`-- run.bat

Key Endpoints

• GET /api/health
• GET /api/symbols
• GET /api/historical/{symbol}
• GET /api/indicators/{symbol}
• GET /api/forecast/{symbol}
• GET /api/market-status
• GET /api/crypto/market
• WS /ws/price/{symbol}

SuperAI Forecast Contract

• Input to every AI model is a single OHLC4 series built as (open + high + low + close) / 4.
• The recommended context length is 512, with model-specific fallback windows when the source history is shorter.
• The default horizon is 10, so each enabled AI model predicts T+1 ... T+10.
• Output from each AI model is an independent future OHLC4 line with quantiles p10, p50, p90.
• API responses expose both last_close (market close) and last_ohlc4 (forecast baseline) so downstream analysis stays explicit and stable.
• Frontend rendering uses one forecast line per model, a shared horizon/timeframe contract, and a versioned asset registry for consistent model/UI alignment.

Health Expectations

When the system is healthy:

• /api/health returns status: online
• timesfm.available is true
• chronos.available is true
• kronos.available is true
• each model reports its own readiness state after warmup or after the first forecast
• the frontend loads from the same backend origin

Troubleshooting

• Install Python 3.11 if it is missing.
• Rebuild venv if it was copied from another machine.
• If forecasts fail, check /api/health and confirm the target model is available and loaded.
• If market data fails, verify connectivity to Binance, Bybit, CoinGecko, Twelve Data, Finnhub, and Yahoo Finance.