app.py

from fastapi import FastAPI
import tensorflow as tf
import joblib
import json
from huggingface_hub import hf_hub_download

app = FastAPI(title="Equilibrium India V1")

MODEL_REPO = "Vansh180/Equilibrium-India-V1" # MODEL repo (not Space)
MODEL_FILENAME = "systemic_risk_model.keras"

# Download model file from model repo into the container filesystem
model_path = hf_hub_download(
    repo_id=MODEL_REPO,
    filename=MODEL_FILENAME,
    repo_type="model"
)

# Load artifacts at startup
model = tf.keras.models.load_model(model_path)
scaler = joblib.load("scaler.pkl")

with open("feature_columns.json") as f:
    feature_columns = json.load(f)

with open("config.json") as f:
    config = json.load(f)

@app.get("/")
def root():
    return {
        "status": "ok",
        "model": "Equilibrium-India-V1",
        "features": feature_columns,
        "tickers": config.get("tickers", []),
        "model_repo": MODEL_REPO
    }

@app.get("/health")
def health():
    return {"status": "healthy"}