Token Classification
Transformers
ONNX
Safetensors
English
Japanese
Chinese
bert
anime
filename-parsing
Eval Results (legacy)
Instructions to use ModerRAS/AniFileBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModerRAS/AniFileBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ModerRAS/AniFileBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ModerRAS/AniFileBERT") model = AutoModelForTokenClassification.from_pretrained("ModerRAS/AniFileBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 22,076 Bytes
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from __future__ import annotations
import json
import subprocess
import sys
import tempfile
import unittest
from pathlib import Path
import tools.annotate_dmhy_dag_agent as agent
def make_args(tmp: Path | None = None, **overrides) -> agent.Args:
values = {
"dag": Path("dag.json"),
"output": Path("out.jsonl"),
"patch_output": (tmp / "patch.jsonl") if tmp is not None else Path("patch.jsonl"),
"units_output": Path("units.jsonl"),
"limit": 10,
"max_requests": 10,
"units_per_request": 10,
"max_context_units": 10,
"workers": 8,
"coverage_mode": agent.COVERAGE_SHARED_ONLY,
"min_incoming_count": 2,
"min_reachable_terminals": 2,
"max_reachable_terminals": 500,
"example_count": 2,
"max_records": 20,
"records_per_terminal": 1,
"terminal_sink_threshold": 1000,
"terminal_cluster_size": 1,
"llm": True,
"base_url": "http://example.test/v1",
"api_key": "test-key",
"model": "gpt-5.4-mini",
"http_timeout": 1,
"retries": 2,
"preserve_i_labels": False,
"resume": False,
}
values.update(overrides)
return agent.Args(**values)
def make_unit(unit_id: str, terminal_ids: list[str]) -> dict:
terminals = [
{
"_terminal_id": terminal_id,
"_terminal_index": index,
"value_examples": [f"Show {terminal_id} 01 [1080P].mkv"],
"suffix_examples": ["01 [1080P]"],
"weight": 1,
}
for index, terminal_id in enumerate(terminal_ids)
]
return {
"unit_id": unit_id,
"node_id": 1,
"kind": "shared_suffix",
"incoming_count": 2,
"reachable_terminals": len(terminal_ids),
"reachable_weight": len(terminal_ids),
"terminal_ids": terminal_ids,
"prefix_examples": ["Show "],
"digit_skeleton_examples": [],
"value_examples": [terminal["value_examples"][0] for terminal in terminals],
"suffix_examples": ["01 [1080P]"],
"common_edge_labels": ["01"],
"_terminals": terminals,
}
def response_for(units: list[dict], wrong_first_id: str | None = None) -> dict:
annotations = []
for index, unit in enumerate(units):
annotations.append(
{
"unit_id": wrong_first_id if index == 0 and wrong_first_id is not None else unit["unit_id"],
"terminal_ids": unit["terminal_ids"],
"episode_title_suffixes": [],
"media_suffixes": ["[1080P]"],
"title_candidates": [],
"llm_label": "media",
"notes": "ok",
}
)
return {"output_text": json.dumps({"annotations": annotations}, ensure_ascii=False)}
class AnnotateDmhyDagAgentTests(unittest.TestCase):
def test_batch_request_schema_contains_annotations_array(self) -> None:
args = make_args()
units = [make_unit("u1", ["t1"]), make_unit("u2", ["t2"])]
body = agent.request_variants(units, args)[0]
schema = body["text"]["format"]["schema"]
self.assertEqual(body["text"]["format"]["name"], "dmhy_dag_batch_annotation")
self.assertIn("annotations", schema["required"])
self.assertEqual(schema["properties"]["annotations"]["items"]["required"][0], "unit_id")
payload = json.loads(body["input"])
self.assertEqual([unit["unit_id"] for unit in payload["units"]], ["u1", "u2"])
def test_batch_mismatch_retries_with_validation_error(self) -> None:
args = make_args(retries=2)
units = [make_unit("u1", ["t1"]), make_unit("u2", ["t2"])]
calls: list[dict] = []
original_post = agent.http_post_json
original_sleep = agent.time.sleep
def fake_post(body, _args):
calls.append(body)
return response_for(units, wrong_first_id="wrong") if len(calls) == 1 else response_for(units)
try:
agent.http_post_json = fake_post
agent.time.sleep = lambda _seconds: None
patches = agent.annotate_batch(units, args, use_llm=True)
finally:
agent.http_post_json = original_post
agent.time.sleep = original_sleep
self.assertEqual(len(calls), 2)
self.assertIn("Previous attempt failed validation", calls[1]["instructions"])
self.assertEqual([patch["unit_id"] for patch in patches], ["u1", "u2"])
self.assertTrue(all(patch["source"] == agent.LLM_SOURCE for patch in patches))
self.assertTrue(all(not patch["fallback"] for patch in patches))
def test_resume_skips_existing_completed_units_and_keeps_order(self) -> None:
with tempfile.TemporaryDirectory() as tmpdir:
tmp = Path(tmpdir)
args = make_args(tmp, resume=True, units_per_request=10, max_context_units=10, workers=1)
units = [make_unit("u1", ["t1"]), make_unit("u2", ["t2"])]
args.patch_output.write_text(
json.dumps(
{
"unit_id": "u1",
"terminal_ids": ["t1"],
"episode_title_suffixes": ["Finale"],
"media_suffixes": [],
"title_candidates": [],
"llm_label": "title",
"notes": "existing",
"source": agent.LLM_SOURCE,
"fallback": False,
"status": "ok",
"attempts": 1,
"errors": [],
},
ensure_ascii=False,
)
+ "\n",
encoding="utf-8",
)
calls: list[list[str]] = []
original_post = agent.http_post_json
def fake_post(body, _args):
payload = json.loads(body["input"])
calls.append([unit["unit_id"] for unit in payload["units"]])
return response_for([units[1]])
try:
agent.http_post_json = fake_post
completed, skipped, llm_requested, pending_unprocessed = agent.annotate_units(units, args)
finally:
agent.http_post_json = original_post
self.assertEqual(skipped, 1)
self.assertEqual(llm_requested, 1)
self.assertEqual(pending_unprocessed, 0)
self.assertEqual(calls, [["u2"]])
patches = [patch for _unit, patch in completed]
self.assertEqual([patch["unit_id"] for patch in patches], ["u1", "u2"])
self.assertEqual(patches[0]["episode_title_suffixes"], ["Finale"])
def test_max_requests_partial_does_not_fallback_unprocessed_units(self) -> None:
args = make_args(max_requests=1, units_per_request=2, max_context_units=2, workers=1)
units = [make_unit("u1", ["t1"]), make_unit("u2", ["t2"]), make_unit("u3", ["t3"])]
calls: list[list[str]] = []
original_post = agent.http_post_json
def fake_post(body, _args):
payload = json.loads(body["input"])
batch_units = [unit for unit in units if unit["unit_id"] in {item["unit_id"] for item in payload["units"]}]
calls.append([unit["unit_id"] for unit in payload["units"]])
return response_for(batch_units)
try:
agent.http_post_json = fake_post
completed, skipped, llm_requested, pending_unprocessed = agent.annotate_units(units, args)
finally:
agent.http_post_json = original_post
self.assertEqual(skipped, 0)
self.assertEqual(llm_requested, 1)
self.assertEqual(pending_unprocessed, 1)
self.assertEqual(calls, [["u1", "u2"]])
patches = [patch for _unit, patch in completed]
self.assertEqual([patch["unit_id"] for patch in patches], ["u1", "u2"])
self.assertTrue(all(not patch["fallback"] for patch in patches))
def test_resume_continues_with_next_unfinished_batch(self) -> None:
with tempfile.TemporaryDirectory() as tmpdir:
tmp = Path(tmpdir)
args = make_args(tmp, resume=True, max_requests=1, units_per_request=1, max_context_units=1, workers=1)
units = [make_unit("u1", ["t1"]), make_unit("u2", ["t2"]), make_unit("u3", ["t3"])]
args.patch_output.write_text(
json.dumps(
{
"unit_id": "u1",
"terminal_ids": ["t1"],
"episode_title_suffixes": [],
"media_suffixes": ["[1080P]"],
"title_candidates": [],
"llm_label": "media",
"notes": "existing",
"source": agent.LLM_SOURCE,
"fallback": False,
"status": "ok",
"attempts": 1,
"errors": [],
},
ensure_ascii=False,
)
+ "\n",
encoding="utf-8",
)
calls: list[list[str]] = []
original_post = agent.http_post_json
def fake_post(body, _args):
payload = json.loads(body["input"])
calls.append([unit["unit_id"] for unit in payload["units"]])
return response_for([units[1]])
try:
agent.http_post_json = fake_post
completed, skipped, llm_requested, pending_unprocessed = agent.annotate_units(units, args)
finally:
agent.http_post_json = original_post
self.assertEqual(skipped, 1)
self.assertEqual(llm_requested, 1)
self.assertEqual(pending_unprocessed, 1)
self.assertEqual(calls, [["u2"]])
self.assertEqual([unit["unit_id"] for unit, _patch in completed], ["u1", "u2"])
def test_cli_heuristic_sample_skips_terminal_sink_and_writes_dataset_rows(self) -> None:
with tempfile.TemporaryDirectory() as tmpdir:
tmp = Path(tmpdir)
dag_path = tmp / "dag.json"
output_path = tmp / "dmhy_weak.dag_sample.jsonl"
patch_path = tmp / "patch.jsonl"
units_path = tmp / "units.jsonl"
dag_path.write_text(
json.dumps(
{
"root": 0,
"nodes": [
{
"id": 0,
"children": [{"label": "[A] Test Show - 0", "target": 1}],
},
{
"id": 1,
"terminal": False,
"children": [{"label": "1 [1080P][WEB-DL]", "target": 2}],
"incoming_count": 2,
"reachable_terminals": 2,
"reachable_weight": 2,
},
{
"id": 2,
"terminal": True,
"children": [],
"incoming_count": 10,
"reachable_terminals": 100,
},
],
"terminals": [
{
"terminal_id": "t0",
"node_id": 1,
"prefix": "[A] Test Show - 0",
"weight": 1,
"suffix_examples": ["1 [1080P][WEB-DL]"],
"value_examples": ["[A] Test Show - 01 [1080P][WEB-DL].mkv"],
},
{
"terminal_id": "t1",
"node_id": 1,
"prefix": "[A] Test Show - 0",
"weight": 1,
"suffix_examples": ["2 [1080P][WEB-DL]"],
"value_examples": ["[A] Test Show - 02 [1080P][WEB-DL].mkv"],
},
],
},
ensure_ascii=False,
),
encoding="utf-8",
)
run = subprocess.run(
[
sys.executable,
"-m",
"tools.annotate_dmhy_dag_agent",
"--dag",
str(dag_path),
"--output",
str(output_path),
"--patch-output",
str(patch_path),
"--units-output",
str(units_path),
"--limit",
"1",
"--max-requests",
"0",
"--workers",
"2",
],
check=False,
capture_output=True,
text=True,
)
self.assertEqual(run.returncode, 0, run.stderr)
patches = [json.loads(line) for line in patch_path.read_text(encoding="utf-8").splitlines()]
self.assertEqual(len(patches), 1)
self.assertEqual(patches[0]["unit_id"], "dag-node-1")
self.assertEqual(patches[0]["terminal_ids"], ["t0", "t1"])
units = [json.loads(line) for line in units_path.read_text(encoding="utf-8").splitlines()]
self.assertEqual(len(units), 1)
self.assertEqual(
set(units[0]),
{
"unit_id",
"source_kind",
"source_id",
"terminal_ids",
"weight",
"context",
"examples",
"expected_output",
},
)
self.assertEqual(units[0]["source_kind"], "prefix_dag")
self.assertEqual(units[0]["source_id"], "1")
self.assertEqual(units[0]["terminal_ids"], ["t0", "t1"])
self.assertEqual(units[0]["weight"], 2)
self.assertEqual(units[0]["context"]["prefixes"], ["[A] Test Show - 0"])
self.assertEqual(units[0]["context"]["digit_skeletons"], [])
self.assertEqual(units[0]["context"]["edge_labels"], ["1 [1080P][WEB-DL]"])
self.assertIn("incoming_count=2", units[0]["context"]["notes"])
self.assertEqual(
units[0]["examples"]["values"],
[
"[A] Test Show - 01 [1080P][WEB-DL].mkv",
"[A] Test Show - 02 [1080P][WEB-DL].mkv",
],
)
self.assertEqual(units[0]["examples"]["suffixes"], ["1 [1080P][WEB-DL]", "2 [1080P][WEB-DL]"])
self.assertEqual(units[0]["expected_output"], {"schema_version": "dmhy-annotation-v1"})
rows = [json.loads(line) for line in output_path.read_text(encoding="utf-8").splitlines()]
self.assertEqual(len(rows), 2)
self.assertEqual(rows[0]["tokens"][0], "[")
self.assertTrue(all(label == "O" or label.startswith("B-") for row in rows for label in row["labels"]))
def test_cli_all_terminals_adds_terminal_cluster_for_uncovered_terminal(self) -> None:
with tempfile.TemporaryDirectory() as tmpdir:
tmp = Path(tmpdir)
dag_path = tmp / "dag.json"
output_path = tmp / "dmhy_weak.dag_all.jsonl"
patch_path = tmp / "patch.jsonl"
units_path = tmp / "units.jsonl"
dag_path.write_text(
json.dumps(
{
"root": 0,
"nodes": [
{
"id": 0,
"children": [
{"label": "A shared", "target": 1},
{"label": "B solo", "target": 4},
],
},
{
"id": 1,
"children": [
{"label": " 01", "target": 2},
{"label": " 02", "target": 3},
],
"incoming_count": 2,
"reachable_terminals": 2,
"reachable_weight": 20,
},
{
"id": 2,
"children": [],
"incoming_count": 1,
"reachable_terminals": 1,
"reachable_weight": 10,
},
{
"id": 3,
"children": [],
"incoming_count": 1,
"reachable_terminals": 1,
"reachable_weight": 10,
},
{
"id": 4,
"children": [],
"incoming_count": 1,
"reachable_terminals": 1,
"reachable_weight": 5,
},
],
"terminals": [
{
"terminal_id": "t0",
"node_id": 2,
"prefix": "Shared Show 01",
"weight": 10,
"suffix_examples": [" [1080P]"],
"value_examples": ["Shared Show 01 [1080P].mkv"],
},
{
"terminal_id": "t1",
"node_id": 3,
"prefix": "Shared Show 02",
"weight": 10,
"suffix_examples": [" [1080P]"],
"value_examples": ["Shared Show 02 [1080P].mkv"],
},
{
"terminal_id": "t2",
"node_id": 4,
"prefix": "Solo Show 03",
"weight": 5,
"suffix_examples": [" [WEB-DL]"],
"value_examples": ["Solo Show 03 [WEB-DL].mkv"],
},
],
},
ensure_ascii=False,
),
encoding="utf-8",
)
run = subprocess.run(
[
sys.executable,
"-m",
"tools.annotate_dmhy_dag_agent",
"--dag",
str(dag_path),
"--output",
str(output_path),
"--patch-output",
str(patch_path),
"--units-output",
str(units_path),
"--coverage-mode",
"all-terminals",
"--min-incoming-count",
"2",
"--min-reachable-terminals",
"2",
"--limit",
"100",
"--max-requests",
"0",
],
check=False,
capture_output=True,
text=True,
)
self.assertEqual(run.returncode, 0, run.stderr)
summary = json.loads(run.stdout)
self.assertEqual(summary["coverage_mode"], "all-terminals")
self.assertEqual(summary["dag_terminals"], 3)
self.assertEqual(summary["unique_terminal_coverage"], 3)
patches = [json.loads(line) for line in patch_path.read_text(encoding="utf-8").splitlines()]
self.assertEqual([patch["kind"] for patch in patches], ["shared_suffix", "terminal_cluster"])
self.assertEqual(patches[0]["terminal_ids"], ["t0", "t1"])
self.assertEqual(patches[1]["terminal_ids"], ["t2"])
units = [json.loads(line) for line in units_path.read_text(encoding="utf-8").splitlines()]
self.assertEqual(len(units), 2)
self.assertEqual(units[0]["unit_id"], "dag-node-1")
self.assertEqual(units[0]["terminal_ids"], ["t0", "t1"])
self.assertEqual(units[1]["unit_id"], "terminal-cluster-1")
self.assertEqual(units[1]["source_kind"], "prefix_dag")
self.assertEqual(units[1]["source_id"], "terminal-cluster-1")
self.assertEqual(units[1]["terminal_ids"], ["t2"])
self.assertIn("kind=terminal_cluster", units[1]["context"]["notes"])
self.assertEqual(
{terminal_id for unit in units for terminal_id in unit["terminal_ids"]},
{"t0", "t1", "t2"},
)
rows = [json.loads(line) for line in output_path.read_text(encoding="utf-8").splitlines()]
self.assertEqual({row["terminal_id"] for row in rows}, {"t0", "t1", "t2"})
self.assertIn("terminal-cluster-1", {row["unit_id"] for row in rows})
if __name__ == "__main__":
unittest.main()
|