Asfmq
0ba85d7749
代码质量：
- 新增 .prettierrc + eslint-plugin-prettier，全量格式化所有 TSX/TS/CSS 文件
- npm scripts 新增 format / format:check / lint:fix
Logo 重设计：
- SVG logo 从简单星月改为望远镜+轨道+三角架+星光，favicon 同步更新
Library 服务端分页与多维筛选：
- LibraryQueryParams 支持 q(全局搜索)/status(下载状态)/doctype/author/year/journal/sort_by
- API 返回 {items, total}，默认每页 12 条
- 前端新增筛选面板：搜索栏、状态下拉、文献类型、排序、分页控件
Agent 工具输出可视化：
- 新增 SpecialToolRenderers.tsx：query_target 天体参数卡片(含 SIMBAD/VizieR 链接)、search_papers
文献列表(内嵌下载/阅读/星系跳转按钮)
- 系统内部工具(compress_context 等)无错误时自动隐藏，减少时间线噪音
- ToolCallCard 与 Reader/Citation 打通：可在工具输出中直接打开文献或跳转引用星系
.agent 目录统一：
- memory/tool-results/trajectories/images 全部归入 library/.agent/ 子目录
PDF 加载修复：
- BilingualViewer 改用 fetch → blob:// URL 加载 PDF，绕过 iframe SameSite Cookie 限制
41 lines
1.6 KiB
Python
41 lines
1.6 KiB
Python
import sqlite3
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import json
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conn = sqlite3.connect('./library/astro_research.db')
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cursor = conn.cursor()
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cursor.execute("SELECT bibcode, title, authors, year, pub, keywords, abstract, doi, arxiv_id, citation_count, reference_count, pdf_path, html_path, markdown_path, translation_path, doctype FROM papers ORDER BY created_at DESC LIMIT 2000")
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rows = cursor.fetchall()
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columns = [c[0] for c in cursor.description]
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data = []
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for r in rows:
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row_dict = dict(zip(columns, r))
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# Parse JSON strings
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try:
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row_dict['authors'] = json.loads(row_dict['authors']) if row_dict['authors'] else []
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except:
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row_dict['authors'] = []
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try:
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row_dict['keywords'] = json.loads(row_dict['keywords']) if row_dict['keywords'] else []
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except:
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row_dict['keywords'] = []
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# map database fields to StandardPaper
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row_dict['pub_journal'] = row_dict.pop('pub')
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row_dict['abstract_text'] = row_dict.pop('abstract')
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row_dict['is_downloaded'] = bool(row_dict['pdf_path'] or row_dict['html_path'])
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row_dict['has_pdf'] = bool(row_dict['pdf_path'])
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row_dict['has_html'] = bool(row_dict['html_path'])
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row_dict['has_markdown'] = bool(row_dict['markdown_path'])
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row_dict['has_translation'] = bool(row_dict['translation_path'])
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row_dict['has_vector'] = False # placeholder
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row_dict['pdf_error'] = None
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row_dict['html_error'] = None
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data.append(row_dict)
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json_str = json.dumps(data, ensure_ascii=False)
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print("Row count:", len(data))
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print("Total JSON bytes:", len(json_str.encode('utf-8')))
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print("Avg bytes per row:", len(json_str.encode('utf-8')) / len(data))
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conn.close()
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