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This runner is intentionally separate from the prefix-tree annotation scripts.
It selects shared DAG suffix units, asks an OpenAI-compatible Responses API for
strict JSON annotations, falls back to deterministic heuristics on failure, and
emits both terminal patch rows and dmhy_weak-compatible sample records.
"""
from __future__ import annotations
import argparse
import json
import os
import sys
import time
import urllib.error
import urllib.request
from concurrent.futures import ThreadPoolExecutor, as_completed
from dataclasses import dataclass
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Iterable
from anifilebert.tokenizer import AnimeTokenizer
from tools.annotate_dmhy_prefix_graph import (
heuristic_patch,
normalize_generated_tokens,
string_list,
unique_keep_order,
write_jsonl,
)
from tools.dmhy_dataset import weak_label_filename
DEFAULT_DAG = Path("datasets/AnimeName/dmhy_prefix_dag.json")
DEFAULT_OUTPUT = Path("datasets/AnimeName/dmhy_weak.dag_sample.jsonl")
DEFAULT_PATCH_OUTPUT = Path("datasets/AnimeName/dmhy_prefix_dag.annotations.dag_sample.jsonl")
DEFAULT_UNITS_OUTPUT = Path("datasets/AnimeName/dmhy_prefix_dag.annotation_units.dag_sample.jsonl")
DEFAULT_BASE_URL = "http://10.137.32.209/v1"
DEFAULT_MODEL = "gpt-5.4-mini"
LLM_SOURCE = "responses-dag-v1"
HEURISTIC_SOURCE = "heuristic-dag-v1"
COVERAGE_SHARED_ONLY = "shared-only"
COVERAGE_ALL_TERMINALS = "all-terminals"
@dataclass(frozen=True)
class Args:
dag: Path
output: Path
patch_output: Path
units_output: Path | None
limit: int
max_requests: int
units_per_request: int
max_context_units: int
workers: int
coverage_mode: str
min_incoming_count: int
min_reachable_terminals: int
max_reachable_terminals: int | None
example_count: int
max_records: int
records_per_terminal: int
terminal_sink_threshold: int
terminal_cluster_size: int
llm: bool
base_url: str
api_key: str | None
model: str
http_timeout: int
retries: int
preserve_i_labels: bool
resume: bool
def parse_args() -> Args:
parser = argparse.ArgumentParser(
description="Annotate a small sample of shared DMHY prefix-DAG suffix units"
)
parser.add_argument("--dag", type=Path, default=DEFAULT_DAG)
parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT)
parser.add_argument("--patch-output", type=Path, default=DEFAULT_PATCH_OUTPUT)
parser.add_argument(
"--units-output",
default=str(DEFAULT_UNITS_OUTPUT),
help="Optional selected annotation units JSONL; use empty string to disable",
)
parser.add_argument("--limit", type=int, default=20, help="Maximum DAG units to annotate")
parser.add_argument("--max-requests", type=int, default=20, help="Maximum LLM requests")
parser.add_argument("--units-per-request", type=int, default=10, help="DAG units per Responses API request")
parser.add_argument(
"--max-context-units",
type=int,
default=20,
help="Maximum unit contexts included in one Responses API request",
)
parser.add_argument("--workers", type=int, default=8, help="Concurrent LLM workers")
parser.add_argument(
"--coverage-mode",
choices=[COVERAGE_SHARED_ONLY, COVERAGE_ALL_TERMINALS],
default=COVERAGE_SHARED_ONLY,
help="Select only shared DAG units, or cover every terminal with terminal_cluster fallback units",
)
parser.add_argument("--min-incoming-count", type=int, default=2)
parser.add_argument("--min-reachable-terminals", type=int, default=2)
parser.add_argument(
"--max-reachable-terminals",
type=int,
default=500,
help="Skip very large shared units for sample runs; use 0 to disable",
)
parser.add_argument("--example-count", type=int, default=8)
parser.add_argument("--max-records", type=int, default=200, help="Maximum dataset records to emit")
parser.add_argument("--records-per-terminal", type=int, default=1)
parser.add_argument(
"--terminal-sink-threshold",
type=int,
default=1000,
help="Do not collect terminals from no-outgoing sink nodes above this size",
)
parser.add_argument(
"--terminal-cluster-size",
type=int,
default=1,
help="Number of uncovered terminals per all-terminals fallback cluster",
)
parser.add_argument("--llm", action="store_true", help="Use the Responses API; otherwise heuristics only")
parser.add_argument(
"--base-url",
default=os.environ.get("ANIFILEBERT_LLM_BASE_URL", DEFAULT_BASE_URL),
help="OpenAI-compatible API base URL",
)
parser.add_argument(
"--api-key",
default=os.environ.get("ANIFILEBERT_LLM_API_KEY"),
help="API key; defaults to ANIFILEBERT_LLM_API_KEY",
)
parser.add_argument("--model", default=DEFAULT_MODEL)
parser.add_argument("--http-timeout", type=int, default=120)
parser.add_argument("--retries", type=int, default=3)
parser.add_argument("--preserve-i-labels", action="store_true")
parser.add_argument("--resume", action="store_true", help="Skip ok/fallback unit_ids already in patch output")
ns = parser.parse_args()
units_arg = str(ns.units_output).strip()
return Args(
dag=ns.dag,
output=ns.output,
patch_output=ns.patch_output,
units_output=Path(units_arg) if units_arg else None,
limit=max(0, ns.limit),
max_requests=max(0, ns.max_requests),
units_per_request=max(1, ns.units_per_request),
max_context_units=max(1, ns.max_context_units),
workers=max(1, ns.workers),
coverage_mode=ns.coverage_mode,
min_incoming_count=max(1, ns.min_incoming_count),
min_reachable_terminals=max(1, ns.min_reachable_terminals),
max_reachable_terminals=None if ns.max_reachable_terminals <= 0 else ns.max_reachable_terminals,
example_count=max(1, ns.example_count),
max_records=max(0, ns.max_records),
records_per_terminal=max(1, ns.records_per_terminal),
terminal_sink_threshold=max(1, ns.terminal_sink_threshold),
terminal_cluster_size=max(1, ns.terminal_cluster_size),
llm=ns.llm,
base_url=ns.base_url,
api_key=ns.api_key,
model=ns.model,
http_timeout=max(1, ns.http_timeout),
retries=max(1, ns.retries),
preserve_i_labels=ns.preserve_i_labels,
resume=ns.resume,
)
def load_dag(path: Path) -> dict[str, Any]:
if not path.exists():
raise SystemExit(f"DAG not found: {path}")
try:
dag = json.loads(path.read_text(encoding="utf-8"))
except json.JSONDecodeError as exc:
raise SystemExit(f"invalid DAG JSON in {path}: {exc}") from exc
if not isinstance(dag, dict) or not isinstance(dag.get("nodes"), list):
raise SystemExit(f"invalid DAG schema in {path}: missing nodes list")
if not isinstance(dag.get("terminals"), list):
raise SystemExit(f"invalid DAG schema in {path}: missing terminals list")
return dag
def int_field(row: dict[str, Any], key: str, default: int = 0) -> int:
try:
return int(row.get(key, default) or default)
except (TypeError, ValueError):
return default
def node_id(node: dict[str, Any], fallback: int) -> int:
try:
return int(node.get("id", fallback))
except (TypeError, ValueError):
raise SystemExit(f"invalid node id: {node.get('id')!r}") from None
def terminal_id(terminal: dict[str, Any], fallback: int) -> str:
value = terminal.get("terminal_id", terminal.get("id", fallback))
return str(value)
def has_outgoing_edges(node: dict[str, Any]) -> bool:
return any(isinstance(edge, dict) for edge in node.get("children") or [])
def edge_labels(node: dict[str, Any], limit: int) -> list[str]:
labels: list[str] = []
for edge in node.get("children") or []:
if isinstance(edge, dict) and edge.get("label") is not None:
labels.append(str(edge["label"]))
return unique_keep_order(labels)[:limit]
def build_indexes(
dag: dict[str, Any],
) -> tuple[dict[int, dict[str, Any]], dict[int, list[dict[str, Any]]]]:
nodes: dict[int, dict[str, Any]] = {}
for index, node in enumerate(dag["nodes"]):
if isinstance(node, dict):
nodes[node_id(node, index)] = node
terminals_by_node: dict[int, list[dict[str, Any]]] = {}
for index, terminal in enumerate(dag["terminals"]):
if not isinstance(terminal, dict):
continue
try:
terminal_node_id = int(terminal.get("node_id"))
except (TypeError, ValueError):
continue
row = dict(terminal)
row["_terminal_id"] = terminal_id(row, index)
row["_terminal_index"] = index
terminals_by_node.setdefault(terminal_node_id, []).append(row)
return nodes, terminals_by_node
class ReachableTerminals:
def __init__(
self,
nodes: dict[int, dict[str, Any]],
terminals_by_node: dict[int, list[dict[str, Any]]],
terminal_sink_threshold: int,
) -> None:
self.nodes = nodes
self.terminals_by_node = terminals_by_node
self.terminal_sink_threshold = terminal_sink_threshold
self.memo: dict[int, list[dict[str, Any]]] = {}
self.visiting: set[int] = set()
def get(self, start: int) -> list[dict[str, Any]]:
if start in self.memo:
return self.memo[start]
if start in self.visiting:
raise SystemExit(f"cycle detected while traversing DAG at node {start}")
self.visiting.add(start)
node = self.nodes.get(start, {})
local_terminals = self.terminals_by_node.get(start, [])
is_large_terminal_sink = not has_outgoing_edges(node) and len(local_terminals) >= self.terminal_sink_threshold
found = [] if is_large_terminal_sink else list(local_terminals)
for edge in node.get("children") or []:
if not isinstance(edge, dict):
continue
try:
found.extend(self.get(int(edge.get("target"))))
except (TypeError, ValueError):
continue
self.visiting.remove(start)
deduped = dedupe_terminals(found)
self.memo[start] = deduped
return deduped
def dedupe_terminals(terminals: Iterable[dict[str, Any]]) -> list[dict[str, Any]]:
seen: set[str] = set()
result: list[dict[str, Any]] = []
for terminal in terminals:
tid = str(terminal.get("_terminal_id") or terminal.get("terminal_id") or "")
if not tid or tid in seen:
continue
seen.add(tid)
result.append(terminal)
return result
def aggregate_examples(terminals: Iterable[dict[str, Any]], key: str, limit: int) -> list[str]:
values: list[str] = []
for terminal in terminals:
if key == "prefix":
value = terminal.get("prefix")
if value is not None:
values.append(str(value))
else:
values.extend(string_list(terminal.get(key)))
return unique_keep_order(values)[:limit]
def aggregate_terminal_field(terminals: Iterable[dict[str, Any]], key: str, limit: int) -> list[str]:
values: list[str] = []
for terminal in terminals:
value = terminal.get(key)
if value is not None:
values.append(str(value))
return unique_keep_order(values)[:limit]
def heuristic_unit_patch(unit: dict[str, Any]) -> dict[str, Any]:
episode_titles: list[str] = []
media_suffixes: list[str] = []
title_candidates: list[str] = []
needs_review = False
for terminal in unit["_terminals"]:
patch = heuristic_patch(terminal, int(terminal.get("_terminal_index", 0)))
episode_titles.extend(patch["episode_title_suffixes"])
media_suffixes.extend(patch["media_suffixes"])
title_candidates.extend(patch["title_candidates"])
needs_review = needs_review or bool(patch["needs_llm_review"])
return {
"unit_id": unit["unit_id"],
"terminal_ids": unit["terminal_ids"],
"episode_title_suffixes": unique_keep_order(episode_titles),
"media_suffixes": unique_keep_order(media_suffixes),
"title_candidates": unique_keep_order(title_candidates),
"llm_label": None,
"notes": f"heuristic fallback; terminals={len(unit['terminal_ids'])}; needs_review={needs_review}",
}
def make_unit(
node: dict[str, Any],
node_id_value: int,
terminals: list[dict[str, Any]],
example_count: int,
) -> dict[str, Any]:
terminal_ids = [str(terminal["_terminal_id"]) for terminal in terminals]
reachable_weight = int_field(node, "reachable_weight")
if reachable_weight <= 0:
reachable_weight = sum(int_field(terminal, "weight", int_field(terminal, "count", 1)) for terminal in terminals)
return {
"unit_id": f"dag-node-{node_id_value}",
"node_id": node_id_value,
"kind": "shared_suffix",
"incoming_count": int_field(node, "incoming_count"),
"reachable_terminals": len(terminals),
"reachable_weight": reachable_weight,
"terminal_ids": terminal_ids,
"prefix_examples": aggregate_examples(terminals, "prefix", example_count),
"digit_skeleton_examples": aggregate_terminal_field(terminals, "digit_skeleton", example_count),
"value_examples": aggregate_examples(terminals, "value_examples", example_count),
"suffix_examples": aggregate_examples(terminals, "suffix_examples", example_count),
"common_edge_labels": edge_labels(node, example_count),
"_terminals": terminals,
}
def make_terminal_cluster_unit(
terminals: list[dict[str, Any]],
cluster_index: int,
example_count: int,
) -> dict[str, Any]:
terminal_ids = [str(terminal["_terminal_id"]) for terminal in terminals]
reachable_weight = sum(int_field(terminal, "weight", int_field(terminal, "count", 1)) for terminal in terminals)
return {
"unit_id": f"terminal-cluster-{cluster_index}",
"node_id": None,
"kind": "terminal_cluster",
"incoming_count": 0,
"reachable_terminals": len(terminals),
"reachable_weight": reachable_weight,
"terminal_ids": terminal_ids,
"prefix_examples": aggregate_examples(terminals, "prefix", example_count),
"digit_skeleton_examples": aggregate_terminal_field(terminals, "digit_skeleton", example_count),
"value_examples": aggregate_examples(terminals, "value_examples", example_count),
"suffix_examples": aggregate_examples(terminals, "suffix_examples", example_count),
"common_edge_labels": [],
"_terminals": terminals,
}
def all_terminals(dag: dict[str, Any]) -> list[dict[str, Any]]:
terminals: list[dict[str, Any]] = []
for index, terminal in enumerate(dag["terminals"]):
if not isinstance(terminal, dict):
continue
row = dict(terminal)
row["_terminal_id"] = terminal_id(row, index)
row["_terminal_index"] = index
terminals.append(row)
return dedupe_terminals(terminals)
def candidate_shared_units(
dag: dict[str, Any],
args: Args,
) -> list[dict[str, Any]]:
nodes, terminals_by_node = build_indexes(dag)
reachable = ReachableTerminals(nodes, terminals_by_node, args.terminal_sink_threshold)
root = int(dag.get("root", 0) or 0)
candidates: list[tuple[tuple[int, int, int, int], int, dict[str, Any]]] = []
for current_id, node in nodes.items():
if current_id == root or not has_outgoing_edges(node):
continue
incoming_count = int_field(node, "incoming_count")
reachable_count = int_field(node, "reachable_terminals")
if incoming_count < args.min_incoming_count:
continue
if reachable_count < args.min_reachable_terminals:
continue
if args.max_reachable_terminals is not None and reachable_count > args.max_reachable_terminals:
continue
sort_key = (-incoming_count, -int_field(node, "reachable_weight"), -reachable_count, current_id)
candidates.append((sort_key, current_id, node))
candidates.sort(key=lambda item: item[0])
candidates.sort(key=lambda item: item[0])
units: list[dict[str, Any]] = []
for _sort_key, current_id, node in candidates:
terminals = reachable.get(current_id)
if not terminals:
continue
units.append(make_unit(node, current_id, terminals, args.example_count))
return units
def unique_terminal_coverage(units: Iterable[dict[str, Any]]) -> set[str]:
covered: set[str] = set()
for unit in units:
covered.update(str(terminal_id_value) for terminal_id_value in unit.get("terminal_ids") or [])
return covered
def shared_only_units(dag: dict[str, Any], args: Args) -> list[dict[str, Any]]:
limit = args.limit if args.limit > 0 else 0
return candidate_shared_units(dag, args)[:limit]
def all_terminal_units(dag: dict[str, Any], args: Args) -> list[dict[str, Any]]:
terminals = all_terminals(dag)
terminals_by_id = {str(terminal["_terminal_id"]): terminal for terminal in terminals}
selected: list[dict[str, Any]] = []
covered: set[str] = set()
for unit in candidate_shared_units(dag, args):
unit_terminal_ids = set(unit["terminal_ids"])
if not unit_terminal_ids:
continue
if unit_terminal_ids & covered:
continue
selected.append(unit)
covered.update(unit_terminal_ids)
uncovered = [terminal for terminal in terminals if str(terminal["_terminal_id"]) not in covered]
for start in range(0, len(uncovered), args.terminal_cluster_size):
cluster_terminals = uncovered[start : start + args.terminal_cluster_size]
selected.append(
make_terminal_cluster_unit(
cluster_terminals,
cluster_index=(start // args.terminal_cluster_size) + 1,
example_count=args.example_count,
)
)
covered.update(str(terminal["_terminal_id"]) for terminal in cluster_terminals)
expected_ids = set(terminals_by_id)
if covered != expected_ids:
missing = sorted(expected_ids - covered)[:10]
extra = sorted(covered - expected_ids)[:10]
raise SystemExit(
"all-terminals coverage mismatch: "
f"expected={len(expected_ids)} covered={len(covered)} missing={missing} extra={extra}"
)
return selected
def select_units(dag: dict[str, Any], args: Args) -> list[dict[str, Any]]:
if args.coverage_mode == COVERAGE_ALL_TERMINALS:
return all_terminal_units(dag, args)
return shared_only_units(dag, args)
def annotation_schema() -> dict[str, Any]:
return {
"type": "object",
"additionalProperties": False,
"required": [
"unit_id",
"terminal_ids",
"episode_title_suffixes",
"media_suffixes",
"title_candidates",
"llm_label",
"notes",
],
"properties": {
"unit_id": {"type": "string"},
"terminal_ids": {"type": "array", "items": {"type": "string"}},
"episode_title_suffixes": {"type": "array", "items": {"type": "string"}},
"media_suffixes": {"type": "array", "items": {"type": "string"}},
"title_candidates": {"type": "array", "items": {"type": "string"}},
"llm_label": {"type": ["string", "null"]},
"notes": {"type": "string"},
},
}
def batch_annotation_schema() -> dict[str, Any]:
return {
"type": "object",
"additionalProperties": False,
"required": ["annotations"],
"properties": {
"annotations": {
"type": "array",
"items": annotation_schema(),
}
},
}
def responses_url(base_url: str) -> str:
return base_url.rstrip("/") + "/responses"
def unit_request_context(unit: dict[str, Any]) -> dict[str, Any]:
return {
"unit_id": unit["unit_id"],
"node_id": unit["node_id"],
"terminal_ids": unit["terminal_ids"],
"incoming_count": unit["incoming_count"],
"reachable_terminals": unit["reachable_terminals"],
"reachable_weight": unit["reachable_weight"],
"prefix_examples": unit["prefix_examples"],
"value_examples": unit["value_examples"],
"suffix_examples": unit["suffix_examples"],
"common_edge_labels": unit["common_edge_labels"],
"heuristic_patch": heuristic_unit_patch(unit),
}
def request_variants(units: list[dict[str, Any]], args: Args, previous_error: str | None = None) -> list[dict[str, Any]]:
if not units:
raise ValueError("request_variants requires at least one unit")
instructions = (
"You annotate anime release filename DAG suffix units. Classify only suffix text that is "
"a human episode title into episode_title_suffixes. Put resolution, codec, source, audio, "
"subtitle, language, hash, release, and file-format fragments into media_suffixes. "
"Use title_candidates for possible anime title strings found in prefix/value examples. Return "
"strict JSON matching the supplied schema with one annotation per input unit. Keep unit_id and "
"terminal_ids exactly unchanged for every unit."
)
if previous_error:
instructions += f" Previous attempt failed validation: {previous_error}. Correct only that issue."
input_obj = {
"units": [unit_request_context(unit) for unit in units[: args.max_context_units]],
}
schema = batch_annotation_schema()
base = {
"model": args.model,
"instructions": instructions,
"input": json.dumps(input_obj, ensure_ascii=False),
}
return [
{
**base,
"reasoning": {"effort": "medium"},
"text": {
"format": {
"type": "json_schema",
"name": "dmhy_dag_batch_annotation",
"strict": True,
"schema": schema,
}
},
},
{
**base,
"text": {
"format": {
"type": "json_schema",
"name": "dmhy_dag_batch_annotation",
"strict": True,
"schema": schema,
}
},
},
{
**base,
"tools": [
{
"type": "function",
"name": "submit_dmhy_dag_batch_annotation",
"strict": True,
"parameters": schema,
"description": "Submit strict DMHY DAG suffix annotations for all input units.",
}
],
"tool_choice": {"type": "function", "name": "submit_dmhy_dag_batch_annotation"},
},
]
def http_post_json(payload: dict[str, Any], args: Args) -> dict[str, Any]:
if not args.api_key:
raise RuntimeError("--llm requires --api-key or ANIFILEBERT_LLM_API_KEY")
request = urllib.request.Request(
responses_url(args.base_url),
data=json.dumps(payload, ensure_ascii=False).encode("utf-8"),
headers={
"Authorization": f"Bearer {args.api_key}",
"Content-Type": "application/json",
},
method="POST",
)
try:
with urllib.request.urlopen(request, timeout=args.http_timeout) as response:
raw = response.read().decode("utf-8")
except urllib.error.HTTPError as exc:
body = exc.read().decode("utf-8", errors="replace")
raise RuntimeError(f"Responses API HTTP {exc.code}: {body[:500]}") from exc
except (urllib.error.URLError, OSError) as exc:
raise RuntimeError(f"Responses API request failed: {exc}") from exc
try:
data = json.loads(raw)
except json.JSONDecodeError as exc:
raise RuntimeError(f"Responses API returned invalid JSON envelope: {raw[:500]}") from exc
if not isinstance(data, dict):
raise RuntimeError("Responses API envelope must be a JSON object")
return data
def extract_annotation_payload(data: dict[str, Any]) -> dict[str, Any]:
output_text = data.get("output_text")
if isinstance(output_text, str) and output_text.strip():
return json.loads(strip_json_fence(output_text))
text_chunks: list[str] = []
for item in data.get("output") or []:
if not isinstance(item, dict):
continue
if item.get("type") in {"function_call", "tool_call"}:
arguments = item.get("arguments")
if isinstance(arguments, str) and arguments.strip():
return json.loads(arguments)
if isinstance(arguments, dict):
return arguments
for content in item.get("content") or []:
if not isinstance(content, dict):
continue
text = content.get("text")
if isinstance(text, str):
text_chunks.append(text)
if content.get("type") in {"function_call", "tool_call"}:
arguments = content.get("arguments")
if isinstance(arguments, str) and arguments.strip():
return json.loads(arguments)
if isinstance(arguments, dict):
return arguments
if text_chunks:
return json.loads(strip_json_fence("\n".join(text_chunks)))
raise RuntimeError("Responses API did not include annotation text or tool arguments")
def strip_json_fence(text: str) -> str:
text = text.strip()
if text.startswith("```"):
lines = text.splitlines()
if lines:
lines = lines[1:]
if lines and lines[-1].strip() == "```":
lines = lines[:-1]
return "\n".join(lines).strip()
return text
def validate_annotation(annotation: Any, unit: dict[str, Any]) -> dict[str, Any]:
if not isinstance(annotation, dict):
raise RuntimeError("annotation must be a JSON object")
missing = [key for key in annotation_schema()["required"] if key not in annotation]
if missing:
raise RuntimeError(f"annotation missing required keys: {', '.join(missing)}")
if annotation["unit_id"] != unit["unit_id"]:
raise RuntimeError(f"unit_id mismatch: {annotation['unit_id']!r}")
returned_ids = [str(item) for item in annotation.get("terminal_ids") or []]
if returned_ids != unit["terminal_ids"]:
raise RuntimeError("terminal_ids mismatch")
cleaned = {
"unit_id": unit["unit_id"],
"terminal_ids": unit["terminal_ids"],
"episode_title_suffixes": unique_keep_order(str(item) for item in annotation["episode_title_suffixes"]),
"media_suffixes": unique_keep_order(str(item) for item in annotation["media_suffixes"]),
"title_candidates": unique_keep_order(str(item) for item in annotation["title_candidates"]),
"llm_label": annotation["llm_label"] if annotation["llm_label"] is None else str(annotation["llm_label"]),
"notes": str(annotation["notes"]),
}
return cleaned
def validate_batch_annotation(payload: Any, units: list[dict[str, Any]]) -> list[dict[str, Any]]:
if not isinstance(payload, dict):
raise RuntimeError("batch annotation must be a JSON object")
annotations = payload.get("annotations")
if not isinstance(annotations, list):
raise RuntimeError("batch annotation missing annotations list")
expected_ids = [unit["unit_id"] for unit in units]
returned_ids = [
str(annotation.get("unit_id"))
for annotation in annotations
if isinstance(annotation, dict) and annotation.get("unit_id") is not None
]
if sorted(returned_ids) != sorted(expected_ids) or len(returned_ids) != len(expected_ids):
raise RuntimeError(f"unit_id set mismatch: expected={expected_ids!r} returned={returned_ids!r}")
annotations_by_id: dict[str, Any] = {}
for annotation in annotations:
if not isinstance(annotation, dict):
raise RuntimeError("annotations entries must be JSON objects")
unit_id_value = str(annotation.get("unit_id"))
if unit_id_value in annotations_by_id:
raise RuntimeError(f"duplicate annotation unit_id: {unit_id_value}")
annotations_by_id[unit_id_value] = annotation
cleaned: list[dict[str, Any]] = []
for unit in units:
cleaned.append(validate_annotation(annotations_by_id[unit["unit_id"]], unit))
return cleaned
def annotate_batch(units: list[dict[str, Any]], args: Args, use_llm: bool) -> list[dict[str, Any]]:
if not use_llm:
patches: list[dict[str, Any]] = []
for unit in units:
patch = heuristic_unit_patch(unit)
patch.update({"source": HEURISTIC_SOURCE, "fallback": True, "attempts": 0, "errors": []})
patches.append(patch)
return patches
errors: list[str] = []
for attempt in range(args.retries):
variants = request_variants(units, args, errors[-1] if errors else None)
payload = variants[min(attempt, len(variants) - 1)]
try:
data = http_post_json(payload, args)
annotations = validate_batch_annotation(extract_annotation_payload(data), units)
for annotation in annotations:
annotation.update({"source": LLM_SOURCE, "fallback": False, "attempts": attempt + 1, "errors": []})
return annotations
except (RuntimeError, json.JSONDecodeError, TypeError, ValueError) as exc:
errors.append(str(exc))
time.sleep(min(2.0, 0.25 * (attempt + 1)))
patches = []
for unit in units:
patch = heuristic_unit_patch(unit)
patch.update(
{
"source": HEURISTIC_SOURCE,
"fallback": True,
"attempts": args.retries,
"errors": errors[-3:],
"notes": f"{patch['notes']}; llm_failed_after={args.retries}",
}
)
patches.append(patch)
return patches
def annotate_unit(unit: dict[str, Any], args: Args, use_llm: bool) -> dict[str, Any]:
return annotate_batch([unit], args, use_llm)[0]
def chunk_units(units: list[dict[str, Any]], size: int) -> list[list[dict[str, Any]]]:
return [units[index : index + size] for index in range(0, len(units), size)]
def load_resume_patches(path: Path) -> dict[str, dict[str, Any]]:
if not path.exists():
return {}
completed: dict[str, dict[str, Any]] = {}
for line_number, line in enumerate(path.read_text(encoding="utf-8").splitlines(), 1):
if not line.strip():
continue
try:
row = json.loads(line)
except json.JSONDecodeError as exc:
raise SystemExit(f"invalid resume patch JSON in {path}:{line_number}: {exc}") from exc
if not isinstance(row, dict):
continue
unit_id_value = row.get("unit_id")
if not unit_id_value:
continue
status = row.get("status")
is_legacy_completed = status is None and ("source" in row or "fallback" in row)
is_completed = status in {"ok", "fallback"} or is_legacy_completed
if is_completed:
completed[str(unit_id_value)] = row
return completed
def patch_from_resume_row(unit: dict[str, Any], row: dict[str, Any]) -> dict[str, Any]:
return {
"unit_id": unit["unit_id"],
"terminal_ids": unit["terminal_ids"],
"episode_title_suffixes": unique_keep_order(str(item) for item in row.get("episode_title_suffixes") or []),
"media_suffixes": unique_keep_order(str(item) for item in row.get("media_suffixes") or []),
"title_candidates": unique_keep_order(str(item) for item in row.get("title_candidates") or []),
"llm_label": row.get("llm_label"),
"notes": str(row.get("notes", "")),
"source": str(row.get("source") or HEURISTIC_SOURCE),
"fallback": bool(row.get("fallback", row.get("status") == "fallback")),
"attempts": int_field(row, "attempts"),
"errors": list(row.get("errors") or []),
}
def patch_row(unit: dict[str, Any], patch: dict[str, Any]) -> dict[str, Any]:
fallback = bool(patch["fallback"])
return {
"unit_id": unit["unit_id"],
"node_id": unit["node_id"],
"kind": unit["kind"],
"incoming_count": unit["incoming_count"],
"reachable_terminals": unit["reachable_terminals"],
"reachable_weight": unit["reachable_weight"],
"terminal_ids": patch["terminal_ids"],
"episode_title_suffixes": patch["episode_title_suffixes"],
"media_suffixes": patch["media_suffixes"],
"title_candidates": patch["title_candidates"],
"llm_label": patch["llm_label"],
"notes": patch["notes"],
"source": patch["source"],
"fallback": fallback,
"status": "fallback" if fallback else "ok",
"attempts": patch["attempts"],
"errors": patch["errors"],
"annotated_at": datetime.now(timezone.utc).isoformat(),
}
def unit_source_id(unit: dict[str, Any]) -> str:
node_id_value = unit.get("node_id")
if node_id_value is None:
return str(unit["unit_id"])
return str(node_id_value)
def unit_public_row(unit: dict[str, Any]) -> dict[str, Any]:
return {
"unit_id": unit["unit_id"],
"source_kind": "prefix_dag",
"source_id": unit_source_id(unit),
"terminal_ids": unit["terminal_ids"],
"weight": int(unit["reachable_weight"]),
"context": {
"prefixes": unit["prefix_examples"],
"digit_skeletons": unit["digit_skeleton_examples"],
"edge_labels": unit["common_edge_labels"],
"notes": (
f"kind={unit['kind']}; incoming_count={unit['incoming_count']}; "
f"reachable_terminals={unit['reachable_terminals']}"
),
},
"examples": {
"values": unit["value_examples"],
"suffixes": unit["suffix_examples"],
},
"expected_output": {
"schema_version": "dmhy-annotation-v1",
},
}
def dataset_records(
units: list[dict[str, Any]],
patches: list[dict[str, Any]],
args: Args,
) -> list[dict[str, Any]]:
tokenizer = AnimeTokenizer()
records: list[dict[str, Any]] = []
seen: set[str] = set()
for unit, patch in zip(units, patches):
per_terminal_counts: dict[str, int] = {}
for terminal in unit["_terminals"]:
terminal_id_value = str(terminal["_terminal_id"])
for source_index, filename in enumerate(string_list(terminal.get("value_examples"))):
if len(records) >= args.max_records:
return records
if per_terminal_counts.get(terminal_id_value, 0) >= args.records_per_terminal:
break
if filename in seen:
continue
seen.add(filename)
sample = weak_label_filename(filename, tokenizer)
if sample is None:
continue
tokens, labels = normalize_generated_tokens(
sample["tokens"],
sample["labels"],
preserve_i_labels=args.preserve_i_labels,
)
records.append(
{
"file_id": f"prefix-dag:{unit['unit_id']}:{terminal_id_value}:{source_index}",
"filename": filename,
"tokens": tokens,
"labels": labels,
"terminal_id": terminal_id_value,
"terminal_index": terminal["_terminal_index"],
"unit_id": unit["unit_id"],
"source": patch["source"],
"needs_llm_review": patch["fallback"],
"episode_title_suffixes": patch["episode_title_suffixes"],
"media_suffixes": patch["media_suffixes"],
"title_candidates": patch["title_candidates"],
"annotations": {
"unit_id": unit["unit_id"],
"terminal_id": terminal_id_value,
"terminal_index": terminal["_terminal_index"],
"source": patch["source"],
"fallback": patch["fallback"],
"episode_title_suffixes": patch["episode_title_suffixes"],
"media_suffixes": patch["media_suffixes"],
"title_candidates": patch["title_candidates"],
"llm_label": patch["llm_label"],
"notes": patch["notes"],
},
}
)
per_terminal_counts[terminal_id_value] = per_terminal_counts.get(terminal_id_value, 0) + 1
return records
def annotate_units(
units: list[dict[str, Any]],
args: Args,
) -> tuple[list[tuple[dict[str, Any], dict[str, Any]]], int, int, int]:
resume_rows = load_resume_patches(args.patch_output) if args.resume else {}
results: list[dict[str, Any] | None] = [None] * len(units)
pending: list[tuple[int, dict[str, Any]]] = []
skipped = 0
for index, unit in enumerate(units):
row = resume_rows.get(unit["unit_id"])
if row is not None and [str(item) for item in row.get("terminal_ids") or []] == unit["terminal_ids"]:
results[index] = patch_from_resume_row(unit, row)
skipped += 1
else:
pending.append((index, unit))
batch_size = max(1, min(args.units_per_request, args.max_context_units))
batches = [
([index for index, _unit in batch], [unit for _index, unit in batch])
for batch in chunk_units(pending, batch_size)
]
if args.llm:
runnable_batches = batches[: args.max_requests]
llm_requested = len(runnable_batches)
else:
runnable_batches = batches
llm_requested = 0
with ThreadPoolExecutor(max_workers=args.workers) as executor:
futures = {
executor.submit(annotate_batch, batch_units, args, args.llm): indices
for indices, batch_units in runnable_batches
}
for future in as_completed(futures):
indices = futures[future]
for index, patch in zip(indices, future.result()):
results[index] = patch
completed = [
(unit, patch)
for unit, patch in zip(units, results)
if patch is not None
]
pending_unprocessed = len(units) - len(completed)
return completed, skipped, llm_requested, pending_unprocessed
def main() -> None:
args = parse_args()
if args.llm and not args.api_key:
raise SystemExit("--llm requires --api-key or ANIFILEBERT_LLM_API_KEY")
dag = load_dag(args.dag)
units = select_units(dag, args)
if not units:
raise SystemExit("no DAG units selected; adjust --limit/--min-incoming-count")
completed_pairs, resume_skipped, llm_requested, pending_unprocessed = annotate_units(units, args)
completed_units = [unit for unit, _patch in completed_pairs]
patches = [patch for _unit, patch in completed_pairs]
patch_rows = [patch_row(unit, patch) for unit, patch in completed_pairs]
records = dataset_records(completed_units, patches, args)
patch_count = write_jsonl(args.patch_output, patch_rows)
record_count = write_jsonl(args.output, records)
unit_count = 0
if args.units_output is not None:
unit_count = write_jsonl(args.units_output, (unit_public_row(unit) for unit in units))
fallback_count = sum(1 for patch in patches if patch["fallback"])
terminal_count = len(all_terminals(dag))
unique_coverage_count = len(unique_terminal_coverage(units))
summary = {
"dag": str(args.dag),
"coverage_mode": args.coverage_mode,
"units_output": str(args.units_output) if args.units_output is not None else None,
"patch_output": str(args.patch_output),
"output": str(args.output),
"selected_units": len(units),
"dag_terminals": terminal_count,
"unique_terminal_coverage": unique_coverage_count,
"written_units": unit_count,
"written_patches": patch_count,
"written_records": record_count,
"llm_requested": llm_requested,
"pending_unprocessed": pending_unprocessed,
"units_per_request": args.units_per_request,
"max_context_units": args.max_context_units,
"resume": args.resume,
"resume_skipped": resume_skipped,
"fallback_count": fallback_count,
"workers": args.workers,
"model": args.model if args.llm else None,
}
print(json.dumps(summary, ensure_ascii=False, indent=2))
if fallback_count:
print(f"warning: {fallback_count} unit(s) used heuristic fallback", file=sys.stderr)
if __name__ == "__main__":
main()
|