feat: 进一步改进
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61
data/config/config.toml
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61
data/config/config.toml
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# [调试] 将更改保存到文件
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#persist_to_file = 1
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# [调试] 覆写时间, 设为 -1 以禁用
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#daystamp_override = -1
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#timestamp_override = -1
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# [调试] 一键通过
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#quick_pass = 1
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# 对于每个项目的默认新记忆原子数量
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#scheduled_num = 8
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# UTC 时间戳修正 仅用于 UNIX 日时间戳的生成修正, 单位为秒
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#timezone_offset = +28800 # 中国标准时间 (UTC+8)
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[interface]
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[interface.memorizor]
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autovoice = true # 自动语音播放, 仅限于 recognition 组件
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[algorithm]
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default = "SM-2" # 主要算法; 可选项: SM-2, SM-15M, FSRS
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[puzzles] # 谜题默认配置
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[puzzles.mcq]
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max_riddles_num = 2
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[puzzles.cloze]
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min_denominator = 3
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[paths] # 相对于配置文件的 ".." (即工作目录) 而言 或绝对路径
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nucleon_dir = "./data/nucleon"
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electron_dir = "./data/electron"
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global_dir = "./data/global" # 全局数据路径, SM-15 等算法需要
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orbital_dir = "./data/orbital"
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cache_dir = "./data/cache"
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template_dir = "./data/template"
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[services] # 定义服务到提供者的映射
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audio = "playsound" # 可选项: playsound(通用), termux(仅用于支持 Android Termux), mpg123(TODO)
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tts = "edgetts" # 可选项: edgetts
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llm = "openai" # 可选项: openai
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sync = "webdav" # 可选项: 留空, webdav
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[providers.tts.edgetts] # EdgeTTS 设置
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voice = "zh-CN-XiaoxiaoNeural" # 可选项: zh-CN-YunjianNeural (男声), zh-CN-XiaoxiaoNeural (女声)
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[providers.llm.openai] # 与 OpenAI 相容的语言模型接口服务设置
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url = ""
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key = ""
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[providers.sync.webdav] # WebDAV 同步设置
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url = ""
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username = ""
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password = ""
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remote_path = "/heurams/"
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verify_ssl = true
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[sync]
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1
data/repo/test/algodata.json
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data/repo/test/algodata.json
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{}
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3
data/repo/test/manifest.toml
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3
data/repo/test/manifest.toml
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title = "测试单元: 过秦论"
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author = "__heurams__"
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desc = "高考古诗文: 过秦论"
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17
data/repo/test/payload.toml
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data/repo/test/payload.toml
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["秦孝公据崤函之固, 拥雍州之地,"]
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note = []
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content = "秦孝公/据/崤函/之固/, 拥/雍州/之地,/"
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translation = "秦孝公占据着崤山和函谷关的险固地势,拥有雍州的土地,"
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keyword_note = {"据"="占据", "崤函"="崤山和函谷关", "雍州"="古代九州之一"}
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["君臣固守以窥周室,"]
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note = []
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content = "君臣/固守/以窥/周室,/"
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translation = "君臣牢固地守卫着,借以窥视周王室的权力,"
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keyword_note = {"窥"="窥视"}
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["有席卷天下, 包举宇内, 囊括四海之意, 并吞八荒之心."]
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note = []
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content = "有/席卷/天下/, 包举/宇内/, 囊括/四海/之意/, 并吞/八荒/之心./"
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translation = "有席卷天下,包办天宇之间,囊括四海的意图,并统天下的雄心。"
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keyword_note = {"席卷"="像卷席子一样全部卷进去", "包举"="像打包一样全部拿走", "囊括"="像装口袋一样全部装进去", "八荒"="八方荒远之地"}
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3
data/repo/test/schedule.toml
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data/repo/test/schedule.toml
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quick_review = [["FillBlank", "1.0"], ["SelectMeaning", "0.5"], ["Recognition", "1.0"]]
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recognition = [["Recognition", "1.0"]]
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final_review = [["FillBlank", "0.7"], ["SelectMeaning", "0.7"], ["Recognition", "1.0"]]
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19
data/repo/test/typedef.toml
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data/repo/test/typedef.toml
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["古文句"]
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[annotation]
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note = "笔记"
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keyword_note = "关键词翻译"
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translation = "语句翻译"
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delimiter = "分隔符"
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content = "内容"
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tts_text = "文本转语音文本"
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["common"]
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delimiter = "/"
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tts_text = "eval:payload['content'].replace('/', '')"
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["puzzles"] # 谜题定义
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# 我们称 "Recognition" 为 recognition 谜题的 alia
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"Recognition" = { __origin__ = "recognition", __hint__ = "", primary = "eval:payload['content']", secondary = ["eval:payload['keyword_note']", "eval:payload['note']"], top_dim = ["eval:payload['translation']"] }
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"SelectMeaning" = { __origin__ = "mcq", __hint__ = "eval:payload['content']", primary = "eval:payload['content']", mapping = "eval:payload['keyword_note']", jammer = "eval:list(payload['keyword_note'].values())", max_riddles_num = "eval:default['mcq']['max_riddles_num']", prefix = "选择正确项: " }
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"FillBlank" = { __origin__ = "cloze", __hint__ = "", text = "eval:payload['content']", delimiter = "eval:metadata['formation']['delimiter']", min_denominator = "eval:default['cloze']['min_denominator']"}
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# Nucleon 是 HeurAMS 软件项目使用的基于 TOML 的专有源文件格式, 版本 5
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# 建议使用的 MIME 类型: application/vnd.xyz.imwangzhiyu.heurams-nucleon.v5+toml
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[__metadata__]
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[__metadata__.attribution] # 元信息
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desc = "带有宏支持的空白模板"
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[__metadata__.annotation] # 键批注
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[__metadata__.formation] # 文件配置
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#delimiter = "/"
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#tts_text = "eval:nucleon['content'].replace('/', '')"
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[__metadata__.orbital.puzzles] # 谜题定义
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# 我们称 "Recognition" 为 recognition 谜题的 alia
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#"Recognition" = { __origin__ = "recognition", __hint__ = "", primary = "eval:nucleon['content']", secondary = ["eval:nucleon['keyword_note']", "eval:nucleon['note']"], top_dim = ["eval:nucleon['translation']"] }
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#"SelectMeaning" = { __origin__ = "mcq", __hint__ = "eval:nucleon['content']", mapping = "eval:nucleon['keyword_note']", jammer = "eval:nucleon['keyword_note']", max_riddles_num = "eval:default['mcq']['max_riddles_num']", prefix = "选择正确项: " }
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#"FillBlank" = { __origin__ = "cloze", __hint__ = "", text = "eval:nucleon['content']", delimiter = "eval:metadata['formation']['delimiter']", min_denominator = "eval:default['cloze']['min_denominator']"}
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[__metadata__.orbital.schedule] # 内置的推荐学习方案
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#quick_review = [["FillBlank", "1.0"], ["SelectMeaning", "0.5"], ["recognition", "1.0"]]
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#recognition = [["Recognition", "1.0"]]
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#final_review = [["FillBlank", "0.7"], ["SelectMeaning", "0.7"], ["recognition", "1.0"]]
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