614 lines
24 KiB
Python
614 lines
24 KiB
Python
#!/usr/bin/env python3
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"""
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Generate an AI literature note from Zotero metadata and save it as a Zotero child note.
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Required environment variables:
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AWESOMEGPT_API_KEY DeepSeek/OpenAI-compatible API key
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AWESOMEGPT_BASE_URL Example: https://api.deepseek.com
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AWESOMEGPT_MODEL Example: deepseek-v4-pro
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ZOTERO_API_KEY Zotero Web API key with library write permission
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Optional:
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ZOTERO_USER_ID If omitted, resolved from /keys/current
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Private local config:
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<skill>\config\config.local.json, created by scripts\init_private_config.py
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"""
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from __future__ import annotations
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import argparse
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import html
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import importlib.util
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import json
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import os
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import re
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import sys
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import urllib.error
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import urllib.parse
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import urllib.request
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from pathlib import Path
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from typing import Any
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try:
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sys.stdout.reconfigure(encoding="utf-8")
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sys.stderr.reconfigure(encoding="utf-8")
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except Exception:
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pass
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LOCAL_ZOTERO = "http://127.0.0.1:23119/api/users/0"
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ZOTERO_WEB = "https://api.zotero.org"
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DEFAULT_VAULT = Path.cwd()
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SKILL_DIR = Path(__file__).resolve().parents[1]
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DEFAULT_PRIVATE_CONFIG = SKILL_DIR / "config" / "config.local.json"
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def fail(message: str) -> None:
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print(f"error: {message}", file=sys.stderr)
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raise SystemExit(1)
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def load_dotenv(path: Path) -> None:
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if not path.exists():
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return
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for raw_line in path.read_text(encoding="utf-8").splitlines():
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line = raw_line.strip()
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if not line or line.startswith("#") or "=" not in line:
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continue
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key, value = line.split("=", 1)
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key = key.strip()
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value = value.strip().strip('"').strip("'")
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os.environ.setdefault(key, value)
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def load_private_config(path: Path) -> None:
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if not path.exists():
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return
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try:
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config = json.loads(path.read_text(encoding="utf-8"))
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except json.JSONDecodeError as exc:
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fail(f"invalid private config JSON at {path}: {exc}")
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zotero = config.get("zotero", {}) if isinstance(config.get("zotero"), dict) else {}
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awesomegpt = config.get("awesomegpt", {}) if isinstance(config.get("awesomegpt"), dict) else {}
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mappings = {
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"ZOTERO_API_KEY": zotero.get("api_key"),
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"ZOTERO_USER_ID": zotero.get("user_id"),
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"AWESOMEGPT_API_KEY": awesomegpt.get("api_key"),
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"AWESOMEGPT_BASE_URL": awesomegpt.get("base_url"),
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"AWESOMEGPT_MODEL": awesomegpt.get("model"),
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}
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for key, value in mappings.items():
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if value:
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os.environ.setdefault(key, str(value))
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def zotero_profile_prefs() -> Path | None:
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profiles_ini = Path.home() / "AppData/Roaming/Zotero/Zotero/profiles.ini"
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profiles_root = profiles_ini.parent
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if profiles_ini.exists():
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text = profiles_ini.read_text(encoding="utf-8", errors="replace")
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blocks = re.split(r"\n(?=\[Profile\d+\])", text)
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for block in blocks:
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if "Default=1" not in block:
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continue
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path_match = re.search(r"^Path=(.+)$", block, re.MULTILINE)
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relative_match = re.search(r"^IsRelative=(\d+)$", block, re.MULTILINE)
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if path_match:
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profile_path = Path(path_match.group(1).strip())
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if relative_match and relative_match.group(1) == "1":
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profile_path = profiles_root / profile_path
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prefs = profile_path / "prefs.js"
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if prefs.exists():
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return prefs
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profiles_dir = profiles_root / "Profiles"
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if profiles_dir.exists():
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for prefs in profiles_dir.glob("*/prefs.js"):
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return prefs
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return None
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def load_awesomegpt_prefs(path: Path | None = None) -> None:
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if path is None:
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path = zotero_profile_prefs()
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if path is None:
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return
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if not path.exists():
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return
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text = path.read_text(encoding="utf-8", errors="replace")
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prefs: dict[str, Any] = {}
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for name, raw_value in re.findall(r'user_pref\("([^"]+)",\s*(.*?)\);', text):
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if not name.startswith("extensions.zotero.zoterogpt."):
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continue
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try:
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prefs[name] = json.loads(raw_value)
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except json.JSONDecodeError:
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continue
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settings_raw = prefs.get("extensions.zotero.zoterogpt.settings")
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if isinstance(settings_raw, str):
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try:
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settings = json.loads(settings_raw)
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except json.JSONDecodeError:
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settings = {}
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else:
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settings = {}
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direct_api = prefs.get("extensions.zotero.zoterogpt.api")
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direct_model = prefs.get("extensions.zotero.zoterogpt.model")
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direct_key = prefs.get("extensions.zotero.zoterogpt.secretKey")
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provider = None
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if isinstance(settings, dict):
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provider = settings.get("DeepSeek") or next(
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(value for key, value in settings.items() if key.lower() == "deepseek"),
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None,
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)
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if isinstance(provider, dict):
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os.environ.setdefault("AWESOMEGPT_BASE_URL", provider.get("api") or "")
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os.environ.setdefault("AWESOMEGPT_MODEL", provider.get("model") or "")
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os.environ.setdefault("AWESOMEGPT_API_KEY", provider.get("secretKey") or "")
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if direct_api:
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os.environ.setdefault("AWESOMEGPT_BASE_URL", str(direct_api))
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if direct_model:
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os.environ.setdefault("AWESOMEGPT_MODEL", str(direct_model))
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if direct_key:
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os.environ.setdefault("AWESOMEGPT_API_KEY", str(direct_key))
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def http_json(
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url: str,
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*,
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method: str = "GET",
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headers: dict[str, str] | None = None,
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payload: Any = None,
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timeout: int = 90,
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) -> Any:
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body = None
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req_headers = dict(headers or {})
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if payload is not None:
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body = json.dumps(payload, ensure_ascii=False).encode("utf-8")
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req_headers.setdefault("Content-Type", "application/json")
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request = urllib.request.Request(url, data=body, method=method, headers=req_headers)
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try:
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with urllib.request.urlopen(request, timeout=timeout) as response:
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text = response.read().decode("utf-8", errors="replace")
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if not text:
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return None
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return json.loads(text)
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except urllib.error.HTTPError as exc:
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detail = exc.read().decode("utf-8", errors="replace")
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fail(f"{method} {url} failed: HTTP {exc.code}: {detail[:800]}")
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except urllib.error.URLError as exc:
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fail(f"{method} {url} failed: {exc}")
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def zotero_local(path: str) -> Any:
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url = LOCAL_ZOTERO + path
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return http_json(url, headers={"Zotero-API-Version": "3"}, timeout=20)
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def zotero_local_optional(path: str) -> Any | None:
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url = LOCAL_ZOTERO + path
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request = urllib.request.Request(url, headers={"Zotero-API-Version": "3"})
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try:
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with urllib.request.urlopen(request, timeout=20) as response:
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text = response.read().decode("utf-8", errors="replace")
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return json.loads(text) if text else None
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except (urllib.error.HTTPError, urllib.error.URLError, json.JSONDecodeError):
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return None
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def zotero_web(path: str, *, method: str = "GET", payload: Any = None) -> Any:
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api_key = os.environ.get("ZOTERO_API_KEY")
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if not api_key:
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fail("ZOTERO_API_KEY is required to write Zotero child notes")
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url = ZOTERO_WEB + path
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return http_json(
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url,
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method=method,
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headers={"Zotero-API-Version": "3", "Zotero-API-Key": api_key},
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payload=payload,
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timeout=60,
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)
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def resolve_user_id() -> str:
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explicit = os.environ.get("ZOTERO_USER_ID")
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if explicit:
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return explicit
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current = zotero_web("/keys/current")
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user_id = current.get("userID") if isinstance(current, dict) else None
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if not user_id:
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fail("could not resolve Zotero userID from /keys/current")
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return str(user_id)
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def find_item(item_key: str | None, query: str | None) -> dict[str, Any]:
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if item_key:
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return zotero_local(f"/items/{urllib.parse.quote(item_key)}")
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if not query:
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fail("provide --item-key or --query")
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qs = urllib.parse.urlencode({"q": query, "limit": 5})
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matches = zotero_local(f"/items/top?{qs}")
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if not matches:
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fail(f"no Zotero item matched query: {query}")
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if len(matches) > 1:
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print(f"warning: {len(matches)} matches; using {matches[0].get('key')}", file=sys.stderr)
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return matches[0]
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def find_items(keys: list[str], query: str | None, limit: int) -> list[dict[str, Any]]:
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items: list[dict[str, Any]] = []
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for key in keys:
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items.append(find_item(key, None))
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if query:
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qs = urllib.parse.urlencode({"q": query, "limit": limit})
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matches = zotero_local(f"/items/top?{qs}")
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seen = {item.get("key") for item in items}
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for item in matches or []:
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if item.get("key") not in seen:
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items.append(item)
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seen.add(item.get("key"))
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if not items:
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fail("provide --item-key/--item-keys or --query")
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return items[:limit] if limit else items
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def all_top_items(limit: int = 0) -> list[dict[str, Any]]:
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items: list[dict[str, Any]] = []
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start = 0
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page_limit = 100
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while True:
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qs = urllib.parse.urlencode({"limit": page_limit, "start": start})
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page = zotero_local(f"/items/top?{qs}")
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if not page:
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break
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items.extend(page)
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if limit and len(items) >= limit:
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return items[:limit]
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if len(page) < page_limit:
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break
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start += page_limit
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return items
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def has_existing_ai_note(parent_key: str) -> bool:
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children = zotero_local(f"/items/{urllib.parse.quote(parent_key)}/children")
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for child in children or []:
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data = child.get("data") or {}
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if data.get("itemType") != "note":
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continue
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note = data.get("note") or ""
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if not note and child.get("key"):
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full_note = zotero_local_optional(f"/items/{urllib.parse.quote(child['key'])}")
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note = ((full_note or {}).get("data") or {}).get("note") or ""
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if "AI文献笔记" in note or "AI Literature Note" in note or f"items/{parent_key}" in note:
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return True
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return False
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def export_bibtex(item_key: str) -> str:
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qs = urllib.parse.urlencode({"itemKey": item_key, "format": "bibtex"})
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url = f"{LOCAL_ZOTERO}/items?{qs}"
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request = urllib.request.Request(url, headers={"Zotero-API-Version": "3"})
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with urllib.request.urlopen(request, timeout=20) as response:
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return response.read().decode("utf-8", errors="replace").strip()
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def local_fulltext(parent_key: str, max_chars: int) -> str:
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children = zotero_local(f"/items/{urllib.parse.quote(parent_key)}/children")
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parts: list[str] = []
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for child in children or []:
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data = child.get("data") or {}
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if data.get("itemType") != "attachment":
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continue
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key = child.get("key")
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if not key:
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continue
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fulltext = zotero_local_optional(f"/items/{urllib.parse.quote(key)}/fulltext")
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if not fulltext:
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continue
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content = fulltext.get("content") if isinstance(fulltext, dict) else ""
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if content:
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parts.append(content)
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if sum(len(p) for p in parts) >= max_chars:
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break
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if not parts:
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for child in children or []:
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data = child.get("data") or {}
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if data.get("itemType") != "attachment" or data.get("contentType") != "application/pdf":
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continue
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path = data.get("path")
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if not path:
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key = child.get("key")
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if key:
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full = zotero_local_optional(f"/items/{urllib.parse.quote(key)}")
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path = ((full or {}).get("data") or {}).get("path")
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if not path:
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continue
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extracted = extract_pdf_text(Path(path), max_chars=max_chars)
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if extracted:
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parts.append(extracted)
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break
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text = "\n\n".join(parts)
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return text[:max_chars]
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def template_paths(vault: Path) -> tuple[Path, Path, Path]:
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templates = vault / "00 Templater"
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if not templates.exists():
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fail(f"template directory not found: {templates}")
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files = {path.name: path for path in templates.glob("*.md")}
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def match(prefix: str, contains: str) -> Path:
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candidates = [
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path for name, path in files.items()
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if name.startswith(prefix) and contains in name
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]
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if not candidates:
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candidates = [path for name, path in files.items() if name.startswith(prefix)]
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if not candidates:
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fail(f"missing template file starting with {prefix} in {templates}")
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return candidates[0]
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return (
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match("03", "AI"),
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match("01", ""),
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match("02", ""),
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)
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def extract_pdf_text(path: Path, max_chars: int) -> str:
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if not path.exists():
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return ""
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max_pages = 8
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if importlib.util.find_spec("fitz"):
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import fitz # type: ignore
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chunks = []
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with fitz.open(str(path)) as doc:
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for page in doc[:max_pages]:
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chunks.append(page.get_text("text"))
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if sum(len(chunk) for chunk in chunks) >= max_chars:
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break
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return "\n".join(chunks)[:max_chars]
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if importlib.util.find_spec("pypdf"):
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from pypdf import PdfReader # type: ignore
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reader = PdfReader(str(path))
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chunks = []
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for page in reader.pages[:max_pages]:
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chunks.append(page.extract_text() or "")
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if sum(len(chunk) for chunk in chunks) >= max_chars:
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break
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return "\n".join(chunks)[:max_chars]
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if importlib.util.find_spec("PyPDF2"):
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from PyPDF2 import PdfReader # type: ignore
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reader = PdfReader(str(path))
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chunks = []
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for page in reader.pages[:max_pages]:
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chunks.append(page.extract_text() or "")
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if sum(len(chunk) for chunk in chunks) >= max_chars:
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break
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return "\n".join(chunks)[:max_chars]
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return ""
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def creators_text(creators: list[dict[str, Any]]) -> str:
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names = []
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for creator in creators:
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name = creator.get("name")
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if not name:
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name = " ".join(x for x in [creator.get("firstName"), creator.get("lastName")] if x)
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if name:
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names.append(name)
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return "; ".join(names)
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def build_prompt(item: dict[str, Any], bibtex: str, fulltext: str, vault: Path, mode: str) -> str:
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data = item.get("data") or {}
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prompt_path, research_template_path, review_template_path = template_paths(vault)
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prompt = prompt_path.read_text(encoding="utf-8")
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research_template = research_template_path.read_text(encoding="utf-8")
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review_template = review_template_path.read_text(encoding="utf-8")
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metadata = {
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"zoteroKey": item.get("key"),
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"title": data.get("title"),
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"itemType": data.get("itemType"),
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"authors": creators_text(data.get("creators") or []),
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"publicationTitle": data.get("publicationTitle"),
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"date": data.get("date"),
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"DOI": data.get("DOI"),
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"url": data.get("url"),
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"abstractNote": data.get("abstractNote"),
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}
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source = {
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"metadata": metadata,
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"bibtex": bibtex,
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"indexedFullTextExcerpt": fulltext,
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}
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instructions = [
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prompt,
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"请先判断文献类型：综述型文献或研究型文献。",
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"若为研究型文献，请严格填充下面的研究型模板：",
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research_template,
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"若为综述型文献，请严格填充下面的综述型模板：",
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review_template,
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"请将模板中的 ${topItem.getField('title')} 替换为真实题名，将 ${topItem.key} 替换为 Zotero key。",
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]
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if mode == "deep":
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instructions.extend(
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[
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"这是满血精读模式。请优先追求完整、具体、可复用的文献阅读笔记，而不是短摘要。",
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"每个模板栏目都要充分展开；如果原文提供了材料配比、制备参数、测试条件、器件结构、性能数据、机理解释或对照实验，必须具体写出。",
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"核心数据必须尽量保留数值和单位；不要用'显著提高'、'性能优异'这类空泛表达替代具体结果。",
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"机制部分要写清因果链条：材料/结构设计如何影响微观结构、界面、导电网络、离子/电子传输、力学响应或器件输出。",
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"局限与启发部分要给出可用于后续课题设计的具体启发，而不是泛泛评价。",
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"如果全文摘录中缺少某项信息，请明确写'原文摘录中未提供'，不要编造。",
|
|
]
|
|
)
|
|
instructions.extend(
|
|
[
|
|
"只输出最终 Markdown 笔记，不要输出解释、判断过程或代码围栏。",
|
|
"文献材料如下：",
|
|
json.dumps(source, ensure_ascii=False, indent=2),
|
|
]
|
|
)
|
|
return "\n\n".join(instructions)
|
|
|
|
|
|
def call_llm(prompt: str, max_tokens: int | None = None) -> str:
|
|
api_key = os.environ.get("AWESOMEGPT_API_KEY")
|
|
base_url = (os.environ.get("AWESOMEGPT_BASE_URL") or "").rstrip("/")
|
|
model = os.environ.get("AWESOMEGPT_MODEL")
|
|
if not api_key or not base_url or not model:
|
|
fail("AWESOMEGPT_API_KEY, AWESOMEGPT_BASE_URL, and AWESOMEGPT_MODEL are required")
|
|
if not base_url.endswith("/v1"):
|
|
base_url = base_url + "/v1"
|
|
payload = {
|
|
"model": model,
|
|
"messages": [
|
|
{"role": "system", "content": "You are a materials science literature-note assistant. Output Simplified Chinese Markdown only."},
|
|
{"role": "user", "content": prompt},
|
|
],
|
|
"temperature": 0.3,
|
|
}
|
|
if max_tokens:
|
|
payload["max_tokens"] = max_tokens
|
|
response = http_json(
|
|
base_url + "/chat/completions",
|
|
method="POST",
|
|
headers={"Authorization": f"Bearer {api_key}"},
|
|
payload=payload,
|
|
timeout=180,
|
|
)
|
|
try:
|
|
return response["choices"][0]["message"]["content"].strip()
|
|
except Exception as exc:
|
|
fail(f"unexpected LLM response shape: {exc}; response={response}")
|
|
|
|
|
|
def markdown_to_zotero_html(markdown: str) -> str:
|
|
lines = markdown.strip().splitlines()
|
|
out: list[str] = []
|
|
in_pre = False
|
|
pre_lines: list[str] = []
|
|
for line in lines:
|
|
stripped = line.strip()
|
|
if stripped.startswith("```") or stripped.startswith("~~~"):
|
|
if in_pre:
|
|
out.append("<pre>" + html.escape("\n".join(pre_lines)) + "</pre>")
|
|
pre_lines = []
|
|
in_pre = False
|
|
else:
|
|
in_pre = True
|
|
continue
|
|
if in_pre:
|
|
pre_lines.append(line)
|
|
continue
|
|
if not stripped:
|
|
continue
|
|
heading = re.match(r"^(#{1,6})\s+(.+)$", stripped)
|
|
if heading:
|
|
level = min(len(heading.group(1)), 6)
|
|
out.append(f"<h{level}>{html.escape(heading.group(2))}</h{level}>")
|
|
elif stripped.startswith(">"):
|
|
out.append(f"<blockquote>{html.escape(stripped.lstrip('> ').strip())}</blockquote>")
|
|
elif re.match(r"^[-*]\s+", stripped):
|
|
out.append(f"<p>{html.escape(stripped)}</p>")
|
|
else:
|
|
out.append(f"<p>{html.escape(stripped)}</p>")
|
|
if in_pre:
|
|
out.append("<pre>" + html.escape("\n".join(pre_lines)) + "</pre>")
|
|
return "\n".join(out)
|
|
|
|
|
|
def create_child_note(user_id: str, parent_key: str, markdown: str, dry_run: bool) -> Any:
|
|
note_html = markdown_to_zotero_html(markdown)
|
|
payload = [{"itemType": "note", "parentItem": parent_key, "note": note_html}]
|
|
if dry_run:
|
|
return {"dryRun": True, "payload": payload}
|
|
return zotero_web(f"/users/{user_id}/items", method="POST", payload=payload)
|
|
|
|
|
|
def main() -> None:
|
|
parser = argparse.ArgumentParser()
|
|
parser.add_argument("--item-key", action="append", default=[], help="Zotero top-level item key; can be repeated")
|
|
parser.add_argument("--item-keys", help="Comma/space separated Zotero top-level item keys")
|
|
parser.add_argument("--query", help="Search query; first top-level match is used")
|
|
parser.add_argument("--all", action="store_true", help="Process all top-level Zotero items")
|
|
parser.add_argument("--limit", type=int, default=1, help="Maximum number of items to process")
|
|
parser.add_argument("--fulltext-chars", type=int, default=12000)
|
|
parser.add_argument("--mode", choices=["quick", "deep"], default="quick", help="quick for batch notes; deep for full-detail notes")
|
|
parser.add_argument("--max-tokens", type=int, default=0, help="Optional LLM output token limit; deep mode defaults to 12000")
|
|
parser.add_argument("--skip-existing", action="store_true", help="Skip items that already have a generated AI child note")
|
|
parser.add_argument("--dry-run", action="store_true", help="generate but do not write Zotero note")
|
|
parser.add_argument("--vault", default=str(DEFAULT_VAULT), help="Obsidian vault containing 00 Templater")
|
|
parser.add_argument("--env-file", help="Optional .env path; defaults to <vault>/.env")
|
|
parser.add_argument("--config", default=str(DEFAULT_PRIVATE_CONFIG), help="Private local config JSON")
|
|
args = parser.parse_args()
|
|
|
|
vault = Path(args.vault).expanduser().resolve()
|
|
load_dotenv(Path(args.env_file).expanduser().resolve() if args.env_file else vault / ".env")
|
|
load_private_config(Path(args.config).expanduser().resolve())
|
|
load_awesomegpt_prefs()
|
|
|
|
keys = list(args.item_key)
|
|
if args.item_keys:
|
|
keys.extend([key for key in re.split(r"[\s,]+", args.item_keys.strip()) if key])
|
|
if args.all:
|
|
items = all_top_items(args.limit if args.limit != 1 else 0)
|
|
else:
|
|
items = find_items(keys, args.query, args.limit)
|
|
user_id = resolve_user_id()
|
|
results = []
|
|
for index, item in enumerate(items, 1):
|
|
try:
|
|
key = item.get("key")
|
|
title = (item.get("data") or {}).get("title")
|
|
if not key:
|
|
results.append({"index": index, "status": "skipped", "reason": "missing key", "title": title})
|
|
continue
|
|
if args.skip_existing and has_existing_ai_note(key):
|
|
results.append({"index": index, "itemKey": key, "title": title, "status": "skipped", "reason": "existing AI note"})
|
|
continue
|
|
print(f"[{index}/{len(items)}] generating {key}: {title}", file=sys.stderr)
|
|
bibtex = export_bibtex(key)
|
|
fulltext_chars = args.fulltext_chars
|
|
if args.mode == "deep" and fulltext_chars == 12000:
|
|
fulltext_chars = 80000
|
|
max_tokens = args.max_tokens
|
|
if args.mode == "deep" and not max_tokens:
|
|
max_tokens = 12000
|
|
fulltext = local_fulltext(key, fulltext_chars)
|
|
prompt = build_prompt(item, bibtex, fulltext, vault, args.mode)
|
|
markdown = call_llm(prompt, max_tokens or None)
|
|
result = create_child_note(user_id, key, markdown, args.dry_run)
|
|
results.append({"index": index, "itemKey": key, "title": title, "status": "ok", "result": result})
|
|
except SystemExit as exc:
|
|
results.append({
|
|
"index": index,
|
|
"itemKey": item.get("key"),
|
|
"title": (item.get("data") or {}).get("title"),
|
|
"status": "error",
|
|
"error": str(exc),
|
|
})
|
|
print(f"[{index}/{len(items)}] error; continuing", file=sys.stderr)
|
|
continue
|
|
except Exception as exc:
|
|
results.append({
|
|
"index": index,
|
|
"itemKey": item.get("key"),
|
|
"title": (item.get("data") or {}).get("title"),
|
|
"status": "error",
|
|
"error": repr(exc),
|
|
})
|
|
print(f"[{index}/{len(items)}] error; continuing: {exc}", file=sys.stderr)
|
|
continue
|
|
print(json.dumps(results, ensure_ascii=False, indent=2))
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|