"""
Stub implementations of worker core functions.

Used when WORKER_MODE=stub, allowing development and testing of
Scheduler / Queue / UI without requiring the Kneron Toolchain environment.

Each stub:
- Sleeps to simulate processing time
- Creates a minimal output file
- Returns a result dict matching the real core function signature
"""

import os
import time
from typing import Any, Dict


def process_onnx_core_stub(
    input_paths: Dict[str, str],
    output_path: str,
    parameters: Dict[str, Any],
) -> Dict[str, Any]:
    """Stub ONNX processing: sleep 2s, create a fake out.onnx."""
    file_path = input_paths["file_path"]
    if not os.path.exists(file_path):
        raise FileNotFoundError(f"Input file not found: {file_path}")

    os.makedirs(os.path.dirname(output_path), exist_ok=True)

    time.sleep(2)

    # Create minimal valid-looking output
    with open(output_path, "wb") as f:
        f.write(b"STUB_ONNX_OUTPUT_" + os.path.basename(file_path).encode())

    return {
        "file_path": output_path,
        "file_size": os.path.getsize(output_path),
        "eval_report": "",
        "model_info": {
            "model_id": parameters.get("model_id"),
            "version": parameters.get("version"),
            "platform": parameters.get("platform"),
        },
    }


def process_bie_core_stub(
    input_paths: Dict[str, str],
    output_path: str,
    parameters: Dict[str, Any],
) -> Dict[str, Any]:
    """Stub BIE processing: sleep 3s, create a fake out.bie."""
    onnx_file_path = input_paths["onnx_file_path"]
    data_dir = input_paths["data_dir"]

    if not os.path.exists(onnx_file_path):
        raise FileNotFoundError(f"ONNX file not found: {onnx_file_path}")

    os.makedirs(os.path.dirname(output_path), exist_ok=True)

    # Count ref images (if any)
    img_count = 0
    if os.path.isdir(data_dir):
        img_count = len([f for f in os.listdir(data_dir) if os.path.isfile(os.path.join(data_dir, f))])

    time.sleep(3)

    with open(output_path, "wb") as f:
        f.write(b"STUB_BIE_OUTPUT")

    return {
        "file_path": output_path,
        "file_size": os.path.getsize(output_path),
        "model_info": {
            "model_id": parameters.get("model_id"),
            "version": parameters.get("version"),
            "platform": parameters.get("platform"),
        },
        "analysis_info": {
            "input_name": "stub_input",
            "batch_size": 1,
            "channels": 3,
            "height": 224,
            "width": 224,
        },
        "processed_images": img_count,
    }


def process_nef_core_stub(
    input_paths: Dict[str, str],
    output_path: str,
    parameters: Dict[str, Any],
) -> Dict[str, Any]:
    """Stub NEF processing: sleep 2s, create a fake out.nef."""
    bie_file_path = input_paths["bie_file_path"]

    if not os.path.exists(bie_file_path):
        raise FileNotFoundError(f"BIE file not found: {bie_file_path}")

    os.makedirs(os.path.dirname(output_path), exist_ok=True)

    time.sleep(2)

    with open(output_path, "wb") as f:
        f.write(b"STUB_NEF_OUTPUT")

    return {
        "file_path": output_path,
        "file_size": os.path.getsize(output_path),
        "model_info": {
            "model_id": parameters.get("model_id"),
            "version": parameters.get("version"),
            "platform": parameters.get("platform"),
        },
        "compilation_info": {
            "optimization_level": "stub",
            "memory_usage": "stub",
            "inference_speed": "stub",
        },
    }