mirror of
https://github.com/MrSleeps/jellyfin-scene-search.git
synced 2026-11-15 22:41:28 +00:00
Sleeps
767 lines
26 KiB
Python
767 lines
26 KiB
Python
from __future__ import annotations
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import argparse
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import hashlib
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from pathlib import Path
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from PIL import Image
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from .captioner import (
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OllamaCaptioner,
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ensure_caption_prompt_file,
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ensure_specialist_prompt_file,
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)
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from .config import settings
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from .database import connect, init_db, pack_vector, unpack_vector
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from .embedder import SiglipEmbedder
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from .frames import extract_frames, media_id_for, sha256_file
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from .jellyfin import (
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caption_context_from_tags,
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route_override_from_tags,
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tags_from_json,
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)
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from .jellyfin_index import (
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cmd_jellyfin_index,
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cmd_jellyfin_items,
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cmd_jellyfin_libraries,
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cmd_jellyfin_test,
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)
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from .maintenance import list_media_by_source, remove_media_by_source
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from .meili import Meili
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from .routing import ExplicitContentRouter, apply_context_routing
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from .search_service import SearchService
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from .sync import rebuild_meili
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def format_ts(ms: int) -> str:
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total = ms // 1000
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h, rem = divmod(total, 3600)
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m, s = divmod(rem, 60)
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return f"{h:02d}:{m:02d}:{s:02d}"
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def build_embedder() -> SiglipEmbedder:
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print(f"Loading {settings.model_id} on {settings.device}...")
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return SiglipEmbedder(settings.model_id, settings.device)
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def cmd_init(_: argparse.Namespace) -> None:
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init_db(settings.db_path)
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ensure_caption_prompt_file(settings.caption_prompt_file)
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ensure_specialist_prompt_file(settings.caption_specialist_prompt_file)
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print(f"SQLite ready: {settings.db_path}")
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print(f"General caption prompt: {settings.caption_prompt_file}")
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print(f"Specialist caption prompt: {settings.caption_specialist_prompt_file}")
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def cmd_index_file(args: argparse.Namespace) -> None:
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init_db(settings.db_path)
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path = Path(args.path).expanduser().resolve()
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if not path.is_file():
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raise SystemExit(f"Not a file: {path}")
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interval_ms = int(round(args.interval * 1000))
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stat = path.stat()
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digest = sha256_file(path)
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media_id = media_id_for(path, digest)
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title = args.title or path.stem
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with connect(settings.db_path) as con:
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row = con.execute("SELECT * FROM media WHERE id = ?", (media_id,)).fetchone()
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if (
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row
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and row["content_sha256"] == digest
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and row["interval_ms"] == interval_ms
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and row["model_id"] == settings.model_id
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and not args.force
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):
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count = con.execute("SELECT COUNT(*) FROM frames WHERE media_id = ?", (media_id,)).fetchone()[0]
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print(f"Already indexed: {title} ({count} frames). Use --force to rebuild.")
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return
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out_dir = settings.thumbs_dir / media_id
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print(f"Extracting one frame every {args.interval:g}s from {title!r}...")
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frame_paths = extract_frames(path, out_dir, args.interval)
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if not frame_paths:
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raise SystemExit("ffmpeg produced no frames")
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embedder = build_embedder()
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rows: list[tuple] = []
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dim = None
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for start in range(0, len(frame_paths), settings.batch_size):
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batch_paths = frame_paths[start:start + settings.batch_size]
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images = []
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try:
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for frame_path in batch_paths:
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images.append(Image.open(frame_path).convert("RGB"))
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vectors = embedder.embed_images(images)
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finally:
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for image in images:
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image.close()
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dim = int(vectors.shape[1])
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for offset, (frame_path, vector) in enumerate(zip(batch_paths, vectors, strict=True)):
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frame_number = start + offset
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timestamp_ms = frame_number * interval_ms
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frame_id = hashlib.sha256(f"{media_id}:{timestamp_ms}:{settings.model_id}".encode()).hexdigest()[:40]
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rows.append((
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frame_id,
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media_id,
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frame_number,
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timestamp_ms,
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str(frame_path),
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pack_vector(vector),
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))
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print(f"Embedded {min(start + len(batch_paths), len(frame_paths))}/{len(frame_paths)} frames")
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assert dim is not None
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with connect(settings.db_path) as con:
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con.execute("DELETE FROM media WHERE id = ?", (media_id,))
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con.execute(
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"""
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INSERT INTO media
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(id, source_path, title, content_sha256, size_bytes, mtime_ns,
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interval_ms, model_id, embedding_dim)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
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""",
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(media_id, str(path), title, digest, stat.st_size, stat.st_mtime_ns,
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interval_ms, settings.model_id, dim),
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)
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con.executemany(
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"""
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INSERT INTO frames
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(id, media_id, frame_number, timestamp_ms, thumb_path, embedding_f16)
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VALUES (?, ?, ?, ?, ?, ?)
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""",
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rows,
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)
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print(f"Stored {len(rows)} canonical frame embeddings in {settings.db_path}")
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print("Next: python -m scene_search.cli sync-meili")
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def cmd_sync_meili(_: argparse.Namespace) -> None:
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def report(update: dict) -> None:
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if update.get("stage") == "sync":
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print(
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f"Queued {int(update.get('documents_processed') or 0)} "
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"documents into Meilisearch"
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)
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total = rebuild_meili(progress=report)
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if total:
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print("Meilisearch rebuild complete (tasks may continue briefly inside Meili).")
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else:
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print("Meilisearch cleared; no canonical media remain.")
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def _route_policy() -> str:
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tag_policy = (
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f"force-specialist={settings.jellyfin_force_specialist_tag}|"
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f"force-general={settings.jellyfin_force_general_tag}|"
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f"specialist-tags={','.join(settings.jellyfin_specialist_tags)}"
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)
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if not settings.caption_router_enabled:
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return (
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f"disabled|general={settings.caption_general_model}|{tag_policy}"
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)
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return (
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f"model={settings.caption_router_model}|"
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f"threshold={settings.caption_router_threshold:.6f}|"
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f"context={settings.caption_router_context_seconds:.3f}|"
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f"{tag_policy}"
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)
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def _select_caption_rows(
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args: argparse.Namespace,
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*,
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only_needing_caption: bool,
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) -> list:
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conditions = []
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params: list[object] = []
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if only_needing_caption and not getattr(args, "force", False):
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expected_models = [
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settings.caption_general_model,
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settings.caption_specialist_model,
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]
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placeholders = ",".join("?" for _ in expected_models)
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conditions.append(
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f"(f.caption IS NULL OR f.caption_model IS NULL "
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f"OR f.caption_model NOT IN ({placeholders}) "
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f"OR f.route_policy IS NULL OR f.route_policy != ?)"
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)
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params.extend(expected_models)
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params.append(_route_policy())
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if getattr(args, "media_id", None):
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conditions.append("f.media_id = ?")
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params.append(args.media_id)
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if getattr(args, "title", None):
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conditions.append("m.title = ?")
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params.append(args.title)
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where = f"WHERE {' AND '.join(conditions)}" if conditions else ""
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limit = ""
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if getattr(args, "limit", None) is not None:
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limit = " LIMIT ?"
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params.append(args.limit)
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with connect(settings.db_path) as con:
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return con.execute(
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f"""
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SELECT f.id, f.media_id, f.timestamp_ms, f.thumb_path, f.caption,
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f.caption_model, f.caption_route, f.route_score, f.route_policy,
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m.title, m.jellyfin_tags
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FROM frames f
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JOIN media m ON m.id = f.media_id
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{where}
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ORDER BY m.title, f.timestamp_ms
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{limit}
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""",
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params,
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).fetchall()
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def _route_rows(rows: list, *, verbose: bool = False) -> tuple[list[tuple], int]:
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valid_rows = []
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missing = 0
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for row in rows:
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image_path = Path(row["thumb_path"])
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if not image_path.is_file():
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missing += 1
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print(
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f"SKIP {row['title']} @ {format_ts(int(row['timestamp_ms']))}: "
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f"missing thumbnail {image_path}"
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)
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continue
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valid_rows.append(row)
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if not valid_rows:
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return [], missing
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policy = _route_policy()
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if settings.caption_router_enabled:
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print(
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f"Routing {len(valid_rows)} frame(s) with "
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f"{settings.caption_router_model} on {settings.caption_router_device}..."
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)
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router = ExplicitContentRouter(
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settings.caption_router_model,
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settings.caption_router_device,
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settings.caption_router_batch_size,
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)
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score_values = router.score_paths(
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[Path(row["thumb_path"]) for row in valid_rows]
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)
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scores = {
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str(row["id"]): score
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for row, score in zip(valid_rows, score_values, strict=True)
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}
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route_input = [
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{
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"id": str(row["id"]),
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"media_id": str(row["media_id"]),
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"timestamp_ms": int(row["timestamp_ms"]),
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}
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for row in valid_rows
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]
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decisions = apply_context_routing(
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route_input,
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scores,
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settings.caption_router_threshold,
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int(round(settings.caption_router_context_seconds * 1000)),
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)
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route_model = settings.caption_router_model
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else:
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scores = {str(row["id"]): 0.0 for row in valid_rows}
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decisions = {
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str(row["id"]): ("general", "disabled")
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for row in valid_rows
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}
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route_model = "disabled"
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for row in valid_rows:
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tags = tags_from_json(row["jellyfin_tags"])
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override = route_override_from_tags(
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tags,
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force_specialist_tag=settings.jellyfin_force_specialist_tag,
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force_general_tag=settings.jellyfin_force_general_tag,
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specialist_tags=settings.jellyfin_specialist_tags,
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)
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if override is not None:
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decisions[str(row["id"])] = override
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routed: list[tuple] = []
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with connect(settings.db_path) as con:
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for row in valid_rows:
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frame_id = str(row["id"])
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route, reason = decisions[frame_id]
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score = scores[frame_id]
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con.execute(
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"""
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UPDATE frames
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SET caption_route = ?, caption_route_reason = ?, route_score = ?,
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route_model = ?, route_policy = ?, routed_at = CURRENT_TIMESTAMP
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WHERE id = ?
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""",
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(route, reason, score, route_model, policy, frame_id),
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)
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routed.append((row, route, score, reason))
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if verbose:
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print(
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f"{row['title']} @ {format_ts(int(row['timestamp_ms']))}: "
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f"score={score:.4f} -> {route} ({reason})"
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)
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general_count = sum(1 for _, route, _, _ in routed if route == "general")
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specialist_count = len(routed) - general_count
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if settings.caption_router_enabled:
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print(
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f"Routing complete: {general_count} general, "
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f"{specialist_count} specialist "
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f"(threshold {settings.caption_router_threshold:.2f}, "
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f"context ±{settings.caption_router_context_seconds:g}s)"
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)
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else:
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print(f"Routing disabled: {general_count} frame(s) -> general model")
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return routed, missing
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def _unload_ollama_model(model: str) -> None:
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captioner = OllamaCaptioner(
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settings.ollama_url,
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model,
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settings.caption_timeout_seconds,
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max_tokens=settings.caption_max_tokens,
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)
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try:
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captioner.unload()
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except Exception as exc:
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print(f"WARN could not unload {model}: {exc}")
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def _caption_queue(
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label: str,
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routed_rows: list[tuple],
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model: str,
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prompt: str,
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) -> tuple[int, int]:
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if not routed_rows:
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return 0, 0
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print(f"\n{label}: {len(routed_rows)} frame(s) with {model}")
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captioner = OllamaCaptioner(
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settings.ollama_url,
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model,
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settings.caption_timeout_seconds,
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prompt,
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settings.caption_max_tokens,
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)
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completed = 0
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failed = 0
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try:
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for row, route, score, reason in routed_rows:
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image_path = Path(row["thumb_path"])
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try:
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context_hint = None
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if settings.jellyfin_tag_context:
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context_hint = caption_context_from_tags(
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tags_from_json(row["jellyfin_tags"]),
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control_tags=(
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settings.jellyfin_force_specialist_tag,
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settings.jellyfin_force_general_tag,
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settings.jellyfin_skip_tag,
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),
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)
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caption = captioner.caption(image_path, context_hint=context_hint)
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except Exception as exc:
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failed += 1
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print(
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f"FAIL {row['title']} @ "
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f"{format_ts(int(row['timestamp_ms']))}: {exc}"
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)
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continue
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with connect(settings.db_path) as con:
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con.execute(
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"""
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UPDATE frames
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SET caption = ?, caption_model = ?,
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captioned_at = CURRENT_TIMESTAMP
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WHERE id = ?
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""",
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(caption, model, row["id"]),
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)
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completed += 1
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print(
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f"{completed:4d}/{len(routed_rows)} {row['title']} @ "
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f"{format_ts(int(row['timestamp_ms']))} "
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f"[{route} {score:.3f}/{reason}]: {caption}"
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)
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finally:
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try:
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captioner.unload()
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print(f"Unloaded {model} from Ollama.")
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except Exception as exc:
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print(f"WARN could not unload {model}: {exc}")
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return completed, failed
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def cmd_route(args: argparse.Namespace) -> None:
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init_db(settings.db_path)
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rows = _select_caption_rows(args, only_needing_caption=False)
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if not rows:
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print("No matching frames.")
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return
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_, missing = _route_rows(rows, verbose=True)
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if missing:
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print(f"Routing skipped {missing} frame(s) with missing thumbnails.")
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def cmd_caption(args: argparse.Namespace) -> None:
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init_db(settings.db_path)
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rows = _select_caption_rows(args, only_needing_caption=True)
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if not rows:
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print("No frames need captioning.")
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return
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routed, missing = _route_rows(rows)
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if not routed:
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print(f"No captionable frames ({missing} missing thumbnails).")
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return
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general_prompt = ensure_caption_prompt_file(settings.caption_prompt_file)
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specialist_prompt = ensure_specialist_prompt_file(
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settings.caption_specialist_prompt_file
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)
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general_rows = [
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item
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for item in routed
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if item[1] == "general"
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and (
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args.force
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or item[0]["caption"] is None
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or item[0]["caption_model"] != settings.caption_general_model
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)
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]
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specialist_rows = [
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item
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for item in routed
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if item[1] == "specialist"
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and (
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args.force
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or item[0]["caption"] is None
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or item[0]["caption_model"] != settings.caption_specialist_model
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)
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]
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retained = len(routed) - len(general_rows) - len(specialist_rows)
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if retained:
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print(
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f"Keeping {retained} existing caption(s) because they already use "
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f"the model selected by the router."
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)
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print(f"General prompt: {settings.caption_prompt_file}")
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print(f"Specialist prompt: {settings.caption_specialist_prompt_file}")
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print(f"Ollama: {settings.ollama_url}")
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if general_rows:
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_unload_ollama_model(settings.caption_specialist_model)
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general_done, general_failed = _caption_queue(
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"General queue",
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general_rows,
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settings.caption_general_model,
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general_prompt,
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)
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if specialist_rows:
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_unload_ollama_model(settings.caption_general_model)
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specialist_done, specialist_failed = _caption_queue(
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"Specialist queue",
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specialist_rows,
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settings.caption_specialist_model,
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specialist_prompt,
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)
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completed = general_done + specialist_done
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failed = general_failed + specialist_failed + missing
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print(f"\nCaptioning complete: {completed} saved, {failed} failed/skipped.")
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if args.sync:
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cmd_sync_meili(args)
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elif completed:
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print("Next: python -m scene_search.cli sync-meili")
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def cmd_remove(args: argparse.Namespace) -> None:
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source_kind = args.source.strip().lower()
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matches = list_media_by_source(settings.db_path, source_kind)
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if not matches:
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print(f"No media found with source_kind={source_kind!r}.")
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return
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print(f"Media matching source_kind={source_kind!r}:")
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for item in matches:
|
|
print(f"- {item.title} ({item.media_id})")
|
|
|
|
if not args.yes:
|
|
answer = input(
|
|
f"Remove {len(matches)} media item(s), their frames/captions/vectors, "
|
|
"and cached thumbnails? [y/N] "
|
|
).strip().lower()
|
|
if answer not in {"y", "yes"}:
|
|
print("Cancelled.")
|
|
return
|
|
|
|
removed = remove_media_by_source(
|
|
settings.db_path,
|
|
settings.thumbs_dir,
|
|
source_kind,
|
|
)
|
|
print(f"Removed {len(removed)} media item(s) from the canonical index.")
|
|
|
|
with connect(settings.db_path) as con:
|
|
remaining = int(con.execute("SELECT COUNT(*) FROM media").fetchone()[0])
|
|
|
|
if remaining:
|
|
print("Rebuilding Meilisearch from remaining canonical media...")
|
|
cmd_sync_meili(args)
|
|
else:
|
|
print("No canonical media remain; clearing Meilisearch.")
|
|
meili = Meili(
|
|
settings.meili_url,
|
|
settings.meili_master_key,
|
|
settings.meili_index,
|
|
)
|
|
meili.clear_documents()
|
|
print("Meilisearch cleared.")
|
|
|
|
|
|
def cmd_status(_: argparse.Namespace) -> None:
|
|
init_db(settings.db_path)
|
|
|
|
print("Canonical SQLite")
|
|
print("----------------")
|
|
with connect(settings.db_path) as con:
|
|
media_rows = con.execute(
|
|
"""
|
|
SELECT m.id, m.title, m.interval_ms, m.model_id,
|
|
COUNT(f.id) AS frames,
|
|
SUM(CASE WHEN f.caption IS NOT NULL THEN 1 ELSE 0 END) AS captioned,
|
|
SUM(CASE WHEN f.caption_route = 'specialist' THEN 1 ELSE 0 END)
|
|
AS specialist_routed
|
|
FROM media m
|
|
LEFT JOIN frames f ON f.media_id = m.id
|
|
GROUP BY m.id, m.title, m.interval_ms, m.model_id
|
|
ORDER BY m.title, m.id
|
|
"""
|
|
).fetchall()
|
|
total_frames = sum(int(row["frames"]) for row in media_rows)
|
|
|
|
print(f"Media items: {len(media_rows)}")
|
|
print(f"Frames: {total_frames}")
|
|
if media_rows:
|
|
print()
|
|
for row in media_rows:
|
|
print(
|
|
f"- {row['title']}: {row['frames']} frames, "
|
|
f"{row['captioned']} captioned, "
|
|
f"{row['specialist_routed']} specialist-routed "
|
|
f"({row['interval_ms'] / 1000:g}s interval)"
|
|
)
|
|
|
|
print()
|
|
print("Meilisearch")
|
|
print("-----------")
|
|
meili = Meili(settings.meili_url, settings.meili_master_key, settings.meili_index)
|
|
try:
|
|
stats = meili.stats()
|
|
except Exception as exc:
|
|
print(f"Status: unavailable ({exc})")
|
|
return
|
|
|
|
print(f"Index: {settings.meili_index}")
|
|
print(f"Documents: {stats.get('numberOfDocuments', 'unknown')}")
|
|
print(f"Indexing: {stats.get('isIndexing', 'unknown')}")
|
|
|
|
def cmd_search(args: argparse.Namespace) -> None:
|
|
service = SearchService(
|
|
db_path=settings.db_path,
|
|
meili_url=settings.meili_url,
|
|
meili_master_key=settings.meili_master_key,
|
|
meili_index=settings.meili_index,
|
|
model_id=settings.model_id,
|
|
device=settings.device,
|
|
semantic_ratio=settings.hybrid_semantic_ratio,
|
|
)
|
|
result = service.search(
|
|
args.query,
|
|
scene_limit=args.limit,
|
|
item_limit=args.limit,
|
|
jellyfin_only=False,
|
|
)
|
|
scenes = result["scenes"]
|
|
if not scenes:
|
|
print("No hits")
|
|
return
|
|
|
|
print(f"\nQuery: {args.query!r}\n")
|
|
for i, scene in enumerate(scenes, 1):
|
|
meili_score = scene.get("ranking_score")
|
|
siglip_score = scene.get("siglip_score")
|
|
meili_text = f" meili={meili_score:.4f}" if meili_score is not None else ""
|
|
siglip_text = f" siglip={siglip_score:.4f}" if siglip_score is not None else ""
|
|
print(
|
|
f"{i:2d}. {scene.get('title')} @ "
|
|
f"{format_ts(int(scene.get('timestamp_ms') or 0))}"
|
|
f"{meili_text}{siglip_text}"
|
|
)
|
|
if scene.get("caption"):
|
|
print(f" {scene['caption']}")
|
|
if scene.get("caption_route"):
|
|
route_score = scene.get("route_score")
|
|
score_text = f" score={float(route_score):.3f}" if route_score is not None else ""
|
|
print(f" route={scene['caption_route']}{score_text}")
|
|
if scene.get("jellyfin_item_id"):
|
|
tags = scene.get("tags") or []
|
|
tags_text = f" tags={', '.join(tags)}" if tags else ""
|
|
print(f" jellyfin={scene['jellyfin_item_id']}{tags_text}")
|
|
|
|
|
|
def cmd_serve(_: argparse.Namespace) -> None:
|
|
from .api import main as api_main
|
|
|
|
api_main()
|
|
|
|
|
|
def make_parser() -> argparse.ArgumentParser:
|
|
p = argparse.ArgumentParser(prog="jellyfin-scene-search")
|
|
sub = p.add_subparsers(dest="command", required=True)
|
|
|
|
init = sub.add_parser("init", help="Create the persistent SQLite database")
|
|
init.set_defaults(func=cmd_init)
|
|
|
|
idx = sub.add_parser("index-file", help="Index a local test video")
|
|
idx.add_argument("path")
|
|
idx.add_argument("--title")
|
|
idx.add_argument("--interval", type=float, default=2.0, help="Seconds between test frames (default: 2)")
|
|
idx.add_argument("--force", action="store_true")
|
|
idx.set_defaults(func=cmd_index_file)
|
|
|
|
sync = sub.add_parser("sync-meili", help="Rebuild/feed Meilisearch from canonical SQLite vectors")
|
|
sync.set_defaults(func=cmd_sync_meili)
|
|
|
|
jf_test = sub.add_parser("jellyfin-test", help="Verify Jellyfin API connectivity")
|
|
jf_test.set_defaults(func=cmd_jellyfin_test)
|
|
|
|
jf_libs = sub.add_parser("jellyfin-libraries", help="List Jellyfin media libraries")
|
|
jf_libs.set_defaults(func=cmd_jellyfin_libraries)
|
|
|
|
jf_items = sub.add_parser("jellyfin-items", help="Inspect video items, tags and Trickplay")
|
|
jf_items.add_argument(
|
|
"--library",
|
|
action="append",
|
|
help="Jellyfin library name; repeat to inspect multiple libraries",
|
|
)
|
|
jf_items.add_argument(
|
|
"--all-libraries",
|
|
action="store_true",
|
|
help="Inspect every Jellyfin library visible to the API key",
|
|
)
|
|
jf_items.add_argument(
|
|
"--exclude-library",
|
|
action="append",
|
|
help="Library name to exclude; repeat as needed",
|
|
)
|
|
jf_items.add_argument(
|
|
"--limit",
|
|
type=int,
|
|
help="Maximum number of items to inspect per selected library",
|
|
)
|
|
jf_items.set_defaults(func=cmd_jellyfin_items)
|
|
|
|
jf_index = sub.add_parser("jellyfin-index", help="Index one or more Jellyfin libraries via Trickplay")
|
|
jf_index.add_argument(
|
|
"--library",
|
|
action="append",
|
|
help="Jellyfin library name; repeat to index multiple libraries",
|
|
)
|
|
jf_index.add_argument(
|
|
"--all-libraries",
|
|
action="store_true",
|
|
help="Index every Jellyfin library visible to the API key",
|
|
)
|
|
jf_index.add_argument(
|
|
"--exclude-library",
|
|
action="append",
|
|
help="Library name to exclude; repeat as needed",
|
|
)
|
|
jf_index.add_argument(
|
|
"--limit",
|
|
type=int,
|
|
help="Maximum number of items to index per selected library; disables pruning",
|
|
)
|
|
jf_index.add_argument("--force", action="store_true", help="Rebuild matching Jellyfin items")
|
|
jf_index.set_defaults(func=cmd_jellyfin_index)
|
|
|
|
route = sub.add_parser("route", help="Classify frames and show which caption model they will use")
|
|
route.add_argument("--media-id", help="Only route frames from one media ID")
|
|
route.add_argument("--title", help="Only route frames from one exact media title")
|
|
route.add_argument("--limit", type=int, help="Maximum number of frames to route")
|
|
route.set_defaults(func=cmd_route)
|
|
|
|
caption = sub.add_parser("caption", help="Route frames and generate persistent captions with Ollama")
|
|
caption.add_argument("--media-id", help="Only caption frames from one media ID")
|
|
caption.add_argument("--title", help="Only caption frames from one exact media title")
|
|
caption.add_argument("--limit", type=int, help="Maximum number of frames to caption")
|
|
caption.add_argument("--force", action="store_true", help="Regenerate captions even if already present")
|
|
caption.add_argument("--sync", action="store_true", help="Sync captions to Meilisearch when finished")
|
|
caption.set_defaults(func=cmd_caption)
|
|
|
|
remove = sub.add_parser("remove", help="Remove indexed media by source kind")
|
|
remove.add_argument(
|
|
"--source",
|
|
required=True,
|
|
choices=["file", "jellyfin"],
|
|
help="Source kind to remove",
|
|
)
|
|
remove.add_argument(
|
|
"--yes",
|
|
action="store_true",
|
|
help="Skip the interactive confirmation prompt",
|
|
)
|
|
remove.set_defaults(func=cmd_remove)
|
|
|
|
status = sub.add_parser("status", help="Show canonical SQLite and Meilisearch index status")
|
|
status.set_defaults(func=cmd_status)
|
|
|
|
serve = sub.add_parser("serve", help="Run the local HTTP search API")
|
|
serve.set_defaults(func=cmd_serve)
|
|
|
|
search = sub.add_parser("search", help="Hybrid caption + visual scene search")
|
|
search.add_argument("query")
|
|
search.add_argument("--limit", type=int, default=10)
|
|
search.set_defaults(func=cmd_search)
|
|
|
|
return p
|
|
|
|
|
|
def main() -> None:
|
|
args = make_parser().parse_args()
|
|
args.func(args)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|