1. Clone the repo or copy app.py and requirements.txt

2. Create & activate a virtual environment (recommended):

python -m venv venv
source venv/bin/activate  # Linux/macOS
venv\Scripts\activate     # Windows

#**Install dependencies:**

pip install -r requirements.txt

#**(Optional) Add API keys for Binance and OANDA in a .env file:**

BINANCE_API_KEY=your_binance_api_key
BINANCE_SECRET=your_binance_secret
OANDA_TOKEN=your_oanda_token
OANDA_ACCOUNT_ID=your_oanda_account_id

#**Usage**
Run the Streamlit app:

streamlit run app.py

Click Discover Binance symbols to load symbols
Select symbols for crypto and FX markets
Configure OHLCV bar count, thresholds, and training mode
Click Fetch historical & train model
Review model reports and live predictions

#**Notes**

The app is a demo for prototyping, not production ready.
Model accuracy depends on data quality and chosen parameters.
API keys for Binance and OANDA are optional; without keys, FX data fetching may be limited.
OHLCV data is cached in .cache folder to speed up re-runs.

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If you want me to add deployment instructions or screenshots, just say!
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