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# File: handler.py
# Description: Core module for SAIR Modular Arithmetic Challenge.
# Tech Stack: PyTorch 2.0+, Python 3.10+
# Author: Amey Thakur
# Profile: https://github.com/Amey-Thakur
# Repository: https://github.com/Amey-Thakur/SAIR-MODULAR-ARITHMETIC-CHALLENGE
# License: CC-BY-4.0
# Date: 2026-07-15
# ==============================================================================
import torch
import json
import os
import sys
# Note: In a real HF deployment, this file sits at the root of the HF repository
# and the models/tokenizers would be bundled next to it.
class EndpointHandler:
def __init__(self, path=""):
# self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
# self.tokenizer = Base10Tokenizer()
# config = TransformerConfig(...)
# self.model = TransformerRoPE(config)
# self.model.load_state_dict(load_file(os.path.join(path, "model.safetensors")))
# self.model.to(self.device)
# self.model.eval()
pass
def __call__(self, data: dict):
"""
Receives a dictionary with `inputs` (the equation string).
Returns the predicted modulo output.
"""
inputs = data.pop("inputs", None)
if not inputs:
return {"error": "No inputs provided. Pass an equation like '123*456'."}
# 1. Encode
# idx = self.tokenizer.encode(inputs)
# 2. Generate
# generated = generate(self.model, idx)
# 3. Decode & Parse Scratchpad
# answer = extract_answer(generated)
# Mocking output for structural completeness
answer = "0"
return [{"generated_text": answer}]
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