0 Summary

what would be easiest way so that we modify this demo so that (1) can input and receive data via API call? 
Easiest: wrap M06 with FastAPI.
M07 = HF .pt + local API

1 Output

curl -X 'POST' \
  'http://127.0.0.1:8000/predict' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "x1": 1,
  "x2": 2
}'
{
  "input": [
    1,
    2
  ],
  "output": -0.22262531518936157
}

2 PY scripts

# m07_api.py

import torch
import torch.nn as nn
from fastapi import FastAPI
from pydantic import BaseModel
from huggingface_hub import hf_hub_download

class TinyModel(nn.Module):
    def __init__(self):
        super().__init__()
        self.fc = nn.Linear(2, 1)

    def forward(self, x):
        return self.fc(x)

class InputData(BaseModel):
    x1: float
    x2: float

app = FastAPI()

pt_file = hf_hub_download(
    repo_id="terrytaylorbonn/m06-tiny-pytorch-model",
    filename="m01_tiny_model.pt",
)

model = TinyModel()
model.load_state_dict(torch.load(pt_file))
model.eval()

@app.get("/")
def root():
    return {"status": "M07 API running"}

@app.post("/predict")
def predict(data: InputData):
    x = torch.tensor([[data.x1, data.x2]], dtype=torch.float32)

    with torch.no_grad():
        y = model(x)

    return {
        "input": [data.x1, data.x2],
        "output": y.item()
    }

4 Code with detailed comments

26.0616 (v1 26.0616)