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4379b25 8d0fd38 4379b25 8d0fd38 4379b25 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 | import argparse
import os
import re
import sys
from typing import List, Optional
from agent import BIDSifierAgent
def _read_optional(path: Optional[str]) -> Optional[str]:
if not path:
return None
if not os.path.isfile(path):
raise FileNotFoundError(f"File not found: {path}")
with open(path, "r", encoding="utf-8", errors="ignore") as f:
return f.read()
def parse_commands_from_markdown(markdown: str) -> List[str]:
"""Extract the first bash/sh fenced code block and return one command per line."""
pattern = re.compile(r"```(?:bash|sh)\n(.*?)```", re.DOTALL | re.IGNORECASE)
m = pattern.search(markdown)
if not m:
return []
block = m.group(1)
commands: List[str] = []
for raw in block.splitlines():
line = raw.strip()
if not line or line.startswith("#"):
continue
commands.append(line)
return commands
def _print_commands(commands: List[str]) -> None:
if not commands:
print("(No commands detected in fenced bash block.)")
return
print("\nProposed commands (NOT executed):")
for c in commands:
print(f" {c}")
def prompt_yes_no(question: str, default: bool = False) -> bool:
suffix = "[Y/n]" if default else "[y/N]"
ans = input(f"{question} {suffix} ").strip().lower()
if not ans:
return default
return ans in {"y", "yes"}
def short_divider(title: str) -> None:
print("\n" + "=" * 80)
print(title)
print("=" * 80 + "\n")
def main(argv: Optional[List[str]] = None) -> int:
parser = argparse.ArgumentParser(
prog="bidsifier",
description="Interactive LLM assistant to convert a dataset into BIDS via stepwise shell commands.",
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
parser.add_argument("--dataset-xml", dest="dataset_xml_path", help="Path to dataset structure XML", required=False)
parser.add_argument("--readme", dest="readme_path", help="Path to dataset README file", required=False)
parser.add_argument("--publication", dest="publication_path", help="Path to a publication/notes file", required=False)
parser.add_argument("--output-root", dest="output_root", help="Target BIDS root directory", required=True)
parser.add_argument("--provider", dest="provider", help="Provider name or identifier, default OpeanAI", required=False, default="openai")
parser.add_argument("--model", dest="model", help="Model name to use", default=os.getenv("BIDSIFIER_MODEL", "gpt-4o-mini"))
# Execution is intentionally disabled; we only display commands.
# Keeping --dry-run for backward compatibility (no effect other than display).
parser.add_argument("--dry-run", dest="dry_run", help="Display-only (default behavior)", action="store_true")
args = parser.parse_args(argv)
dataset_xml = _read_optional(args.dataset_xml_path)
readme_text = _read_optional(args.readme_path)
publication_text = _read_optional(args.publication_path)
context = {
"dataset_xml": dataset_xml,
"readme_text": readme_text,
"publication_text": publication_text,
"output_root": args.output_root,
}
command_env = {
"OUTPUT_ROOT": args.output_root,
}
if args.dataset_xml_path:
command_env["DATASET_XML_PATH"] = os.path.abspath(args.dataset_xml_path)
if args.readme_path:
command_env["README_PATH"] = os.path.abspath(args.readme_path)
if args.publication_path:
command_env["PUBLICATION_PATH"] = os.path.abspath(args.publication_path)
agent = BIDSifierAgent(provider=args.provider, model=args.model)
short_divider("Step 1: Understand dataset")
summary = agent.run_step("summary", context)
print(summary)
if not prompt_yes_no("Proceed to create BIDS root?", default=True):
return 0
short_divider("Step 2: Propose commands to create BIDS root")
root_plan = agent.run_step("create_root", context)
print(root_plan)
cmds = parse_commands_from_markdown(root_plan)
_print_commands(cmds)
if not prompt_yes_no("Proceed to create metadata files?", default=True):
return 0
short_divider("Step 3: Propose commands to create metadata files")
meta_plan = agent.run_step("create_metadata", context)
print(meta_plan)
cmds = parse_commands_from_markdown(meta_plan)
_print_commands(cmds)
if not prompt_yes_no("Proceed to create empty BIDS structure?", default=True):
return 0
short_divider("Step 4: Propose commands to create dataset structure")
struct_plan = agent.run_step("create_structure", context)
print(struct_plan)
cmds = parse_commands_from_markdown(struct_plan)
_print_commands(cmds)
if not prompt_yes_no("Proceed to propose renaming/moving?", default=True):
return 0
short_divider("Step 5: Propose commands to rename/move files")
move_plan = agent.run_step("rename_move", context)
print(move_plan)
cmds = parse_commands_from_markdown(move_plan)
_print_commands(cmds)
print("\nAll steps completed. Commands were only displayed (never executed). Use them manually or in a future Gradio/HF Space interface.")
return 0
if __name__ == "__main__":
sys.exit(main())
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