"""
GGUF + DAG Pipeline — load GGUF model, run through networkx DAG
Author: Ahmad Ali Parr · Trust: Bel Esprit D'Accord Irrevocable Trust
"""
# pip install llama_cpp_python networkx
from llama_cpp import Llama
import networkx as nx

model = Llama(model_path="model.gguf", n_ctx=2048, n_threads=8)

# Define DAG
dag = nx.DiGraph()
dag.add_nodes_from(["parse_binary", "convert_numpy", "convert_torch", "inference"])
dag.add_edges_from([
    ("parse_binary", "convert_numpy"),
    ("convert_numpy", "convert_torch"),
    ("convert_torch", "inference"),
])

def parse_binary(path):
    with open(path, "rb") as f:
        return f.read()

def convert_numpy(bin_data):
    import numpy as np
    return np.frombuffer(bin_data, dtype=np.float32)

def convert_torch(np_arr):
    import torch
    return torch.from_numpy(np_arr)

def inference(tensor):
    return model("Translate this sentence to Korean:")

# Execute
binary_data  = parse_binary("model.gguf")
np_arr       = convert_numpy(binary_data)
torch_tensor = convert_torch(np_arr)
output       = inference(torch_tensor)
print(output)