--extra-index-url https://download.pytorch.org/whl/cpu

# --- core data / numerics ---
# floor is 2.1, not just "2.0": the code's resample/date_range rules use the
# lowercase offset aliases ("10min", "4h", "min") -- confirmed these work on
# 2.1.4 through the current 3.0.x, and confirmed pandas 3.0 now HARD-ERRORS
# on the old uppercase forms ("4H", "10T") rather than just warning, so
# lowercase was the right choice; 2.1 is the safe, verified floor for it.
pandas>=2.1
numpy>=1.24

# --- market data (free, no API key) ---
yfinance>=0.2.40

# --- UI & charts ---
gradio>=4.36
plotly>=5.20

# --- ARIMA / Auto-ARIMA / ARIMA-GARCH ---
statsmodels>=0.14
arch>=6.3

# --- Moirai (Salesforce) — https://github.com/SalesforceAIResearch/uni2ts ---
uni2ts
gluonts

# --- TimesFM 2.5 (Google) — https://github.com/google-research/timesfm ---
# [xreg] is only needed for the 10-feature covariate path (models/timesfm_model.py's
# forecast_with_covariates()) -- it pulls in scikit-learn + JAX/jaxlib on top of
# [torch]. Plain Close-only TimesFM forecasting never touches xreg and would work
# fine with just timesfm[torch], but since this project's `features=` support is
# meant to work out of the box, both extras are requested together here.
timesfm[torch,xreg]

# --- shared deep-learning backend ---
torch
einops
huggingface_hub