app.py

"""Hugging Face Spaces entrypoint for the Claims Co-Pilot demo.

Thin wrapper that invokes claims.src.demo.copilot_app_claims.main with
paths relative to the Space repo root. The full app code lives at
claims/src/demo/copilot_app_claims.py.

Three tabs:
  - Claimant Trajectory       (live multi-surface inference on a curated cast)
  - Why this matters for payers (US health-payer P&L vocabulary)
  - How this fits your stack    (VPC, MCP, license-architecture-not-hosted)
"""

import os
import sys
from pathlib import Path

# Make the bundled source tree importable.
HERE = Path(__file__).parent
sys.path.insert(0, str(HERE))

# Point the inference module at the public LFM2 base on the HF Hub. The
# Spaces runner can `from_pretrained()` this id directly; no local download
# step needed.
os.environ.setdefault("CLAIMS_BACKBONE_PATH", "LiquidAI/LFM2.5-350M-Base")

from claims.src.demo.copilot_app_claims import main  # noqa: E402

sys.argv = [
    "app",
    "--admission-config", "claims/configs/train_admission_h100_v3.yaml",
    "--admission-ckpt", "checkpoints/admission_v3_demo.pt",
    "--next-event-config", "claims/configs/train_next_event_h100.yaml",
    "--next-event-ckpt", "checkpoints/next_event_v1_demo.pt",
    "--fraud-config", "claims/configs/train_fraud_h100.yaml",
    "--fraud-ckpt", "checkpoints/fraud_v1_demo.pt",
    "--cache-dir", "claims/data/cache_demo",
    "--cast-path", "claims/data/admission_cast_v2.json",
    "--tokenizer-state", "claims/data/tokenizer_state.json",
    "--backbone-model-path", os.environ["CLAIMS_BACKBONE_PATH"],
    "--device", "cpu",
    "--dtype", "float32",
    "--port", "7860",
]

main()