109 lines
3.9 KiB
Python
109 lines
3.9 KiB
Python
import os
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import json
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from pathlib import Path
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from openai import OpenAI
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from utils import with_disk_cache
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client = OpenAI()
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@with_disk_cache('select_best_torrents')
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def select_best_torrents(torrents_text: str) -> str:
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"""
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Calls the OpenAI API to select the best torrent IDs using a predefined prompt.
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:param torrents_text: A string containing formatted torrent information.
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:return: A string containing the selected torrent IDs, separated by space.
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"""
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prompt_path = Path(__file__).parent / "prompt_select_torrents.json"
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with open(prompt_path, "r", encoding="utf-8") as f:
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messages = json.load(f)
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messages.append({
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"role": "user",
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"content": torrents_text
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})
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response = client.chat.completions.create(
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model="gpt-5.4",
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messages=messages,
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response_format={"type": "text"},
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verbosity="medium",
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reasoning_effort="medium",
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store=True
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)
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return response.choices[0].message.content
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@with_disk_cache('generate_rename_mapping')
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def generate_rename_mapping(directory_text: str) -> dict[str, str]:
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"""
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Calls the OpenAI API to generate a renaming mapping for files
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into a Jellyfin-compatible library format.
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:param directory_text: A string containing the base directory and list of files.
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:return: A dictionary mapping source paths to destination paths.
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"""
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prompt_path = Path(__file__).parent / "prompt_generate_mapping.json"
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with open(prompt_path, "r", encoding="utf-8") as f:
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messages = json.load(f)
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messages.append({
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"role": "user",
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"content": directory_text
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})
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response = client.chat.completions.create(
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model="gpt-5.1-codex-mini",
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messages=messages,
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response_format={"type": "text"},
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reasoning_effort="low",
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store=True
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)
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raw_response = response.choices[0].message.content
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mapping = {}
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for line in raw_response.splitlines():
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if " -->> " in line:
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parts = line.split(" -->> ", 1)
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if len(parts) == 2:
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mapping[parts[0].strip()] = parts[1].strip()
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else:
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print(f"Invalid line: {line}")
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return mapping
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def apply_rename_mapping(mapping: dict[str, str], base_src_dir: str | Path, base_dst_dir: str | Path) -> None:
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"""
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Creates symbolic links from source files to their destinations based on the provided mapping.
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Missing directories in the destination paths will be created automatically.
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:param mapping: Dictionary where keys are source paths and values are destination paths.
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These can be relative to the provided base directories.
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:param base_src_dir: The base directory where the source files reside.
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:param base_dst_dir: The base directory where the symbolic links will be created.
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"""
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src_base = Path(base_src_dir).resolve()
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dst_base = Path(base_dst_dir).resolve()
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for src_rel, dst_rel in mapping.items():
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src_path = src_base / Path(src_rel)
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dst_path = dst_base / Path(dst_rel)
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# Ensure the source actually exists before creating a link to it
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if not src_path.exists():
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print(f"Warning: Source path does not exist, skipping: {src_path}")
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continue
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# Create parent directories for the destination if they don't exist
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dst_path.parent.mkdir(parents=True, exist_ok=True)
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# Create the symbolic link. If it already exists, gracefully ignore or overwrite.
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try:
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if dst_path.exists() or dst_path.is_symlink():
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dst_path.unlink()
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os.symlink(src_path, dst_path)
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print(f"Linked: {dst_path.relative_to(dst_base)} -> {src_path.name}")
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except Exception as e:
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print(f"Failed to link {src_rel} to {dst_rel}: {e}")
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