feat(server): 万象模型的配置链路、模型包解析与按需下载

- [association] 新增五键：sentence_collocation_additive/rerank（设置页开关，默认
  关）、sentence_collocation_model（模型包 id，下载器写回）、两个权重（配置文件
  高级项，不进设置页）；出厂模板与工作配置同步更新，通过五件套映射下发
- 模型包确定性布局 <DataDir>/models/<id>/<id>.gram，解析只是一次 stat；开关开
  着但文件缺席即视为关闭，词格静默降级
- collocation_model.{h,cpp}：WinHTTP 按需下载（重定向放行、进度回报）+ BCrypt
  SHA256 校验 + 同卷原子落位 + CC-BY-4.0 NOTICE。SHA256/字节数在常量里钉死：
  上游 LTS release 会被原地重传，换字节必须显式更新并复跑离线评测
- CandidateSource::Collocation 落库/学习判定与神经整句同类，候选徽标〔万象〕
- 下载器编译进 Server 与独立设置进程两个宿主，状态以磁盘为准

.gitignore

@@ -27,3 +27,10 @@ log.txt
 # 由 scripts/fetch-neural-model.ps1 按 lock.json 从 release 重新取到并校验 sha256。
 /neural-model/*.safetensors
 __pycache__/
+
+# 外部模型包：models/ 下是按需下载的大文件（如万象 .gram 400MB），来源与摘要
+# 记在调研文档与锁文件里，不进仓库。
+/models/
+
+# 本地测试数据暂存（照 scripts/ci/test-server.ps1 的布局手工准备的）
+/stage/

installer/default_config/config.default.toml

@@ -81,8 +81,18 @@ sentence_neural_desktop = false
 sentence_neural_keyboard = true
 # 某个模型的首选与已有候选重复时，改为显示该模型排名最高的下一条不同结果
 sentence_show_next_on_duplicate = false
-# 在候选窗的整句候选后显示来源标签（〔Trigram〕〔Unigram〕〔神经D〕〔神经K〕）
+# 在候选窗的整句候选后显示来源标签（〔Trigram〕〔Unigram〕〔神经D〕〔神经K〕〔万象〕）
 sentence_source_badge = false
+# 万象语法模型（octagram .gram，约 390MB，设置页下载）：字级搭配强度表，与词表零耦合。
+# 两个机制共用一份模型包（models/<id>/<id>.gram），默认全关；模型未下载时开关不生效。
+# additive 在词格解码里逐边叠加搭配分，rerank 在 n-best 上按整句搭配分重排（〔万象〕行）。
+sentence_collocation_additive = false
+sentence_collocation_rerank = false
+# 模型包 id，由设置页下载器写回；也可手动放置后填 id（布局 models/<id>/<id>.gram）
+sentence_collocation_model = ""
+# 搭配项的线性权重（log10 域）。取值依据 docs/research 的离线评测扫描；不进设置页
+sentence_collocation_weight = 0.1
+sentence_collocation_rerank_weight = 0.05
 
 #
 # 腾讯云机器翻译（竖排候选项本地词库未命中时的补全）

server/CMakeLists.txt

@@ -210,6 +210,8 @@ set(SRC_FILES
     "./src/settings/settings_launcher.h"
     "./src/settings/api_credential_test.cpp"
     "./src/settings/api_credential_test.h"
+    "./src/settings/collocation_model.cpp"
+    "./src/settings/collocation_model.h"
     "./src/skin/candidate_skin_catalog.cpp"
     "./src/skin/candidate_skin_catalog.h"
     "./src/session/engine_input_session.cpp"
@@ -432,6 +434,8 @@ add_executable(${SETTINGS_EXECUTABLE_NAME} WIN32
     "./src/settings/settings_app.cpp"
     "./src/settings/api_credential_test.cpp"
     "./src/settings/api_credential_test.h"
+    "./src/settings/collocation_model.cpp"
+    "./src/settings/collocation_model.h"
     "./src/settings/settings_splash.cpp"
     "./src/settings/settings_splash.h"
     "./src/settings/settings_launcher.cpp"

server/assets/config/config.toml

@@ -81,8 +81,18 @@ sentence_neural_desktop = false
 sentence_neural_keyboard = true
 # 某个模型的首选与已有候选重复时，改为显示该模型排名最高的下一条不同结果
 sentence_show_next_on_duplicate = false
-# 在候选窗的整句候选后显示来源标签（〔Trigram〕〔Unigram〕〔神经D〕〔神经K〕）
+# 在候选窗的整句候选后显示来源标签（〔Trigram〕〔Unigram〕〔神经D〕〔神经K〕〔万象〕）
 sentence_source_badge = false
+# 万象语法模型（octagram .gram，约 390MB，设置页下载）：字级搭配强度表，与词表零耦合。
+# 两个机制共用一份模型包（models/<id>/<id>.gram），默认全关；模型未下载时开关不生效。
+# additive 在词格解码里逐边叠加搭配分，rerank 在 n-best 上按整句搭配分重排（〔万象〕行）。
+sentence_collocation_additive = false
+sentence_collocation_rerank = false
+# 模型包 id，由设置页下载器写回；也可手动放置后填 id（布局 models/<id>/<id>.gram）
+sentence_collocation_model = ""
+# 搭配项的线性权重（log10 域）。取值依据 docs/research 的离线评测扫描；不进设置页
+sentence_collocation_weight = 0.1
+sentence_collocation_rerank_weight = 0.05
 
 #
 # 腾讯云机器翻译（候选项本地词库未命中时的补全）

server/src/config/ime_config.cpp

@@ -120,6 +120,13 @@ bool g_assoc_sentence_google = true;
 bool g_assoc_sentence_neural_desktop = false;
 bool g_assoc_sentence_neural_keyboard = true;
 bool g_assoc_sentence_show_next_on_duplicate = false;
+// 万象语法模型（octagram .gram）：两个机制默认全关，模型 id 默认空（未下载/未选）。
+// 权重不进设置页，供配置文件高级调参；取值依据 docs/research 的离线评测扫描。
+bool g_assoc_sentence_collocation_additive = false;
+bool g_assoc_sentence_collocation_rerank = false;
+std::string g_assoc_sentence_collocation_model;
+double g_assoc_sentence_collocation_weight = 0.1;
+double g_assoc_sentence_collocation_rerank_weight = 0.05;
 // 候选窗整句候选后的来源标签（〔Trigram〕〔神经K〕等），默认不显示。
 bool g_assoc_sentence_source_badge = false;
 bool g_emoji_mixed_input_enabled = false;
@@ -491,6 +498,12 @@ bool LoadImeConfig()
         g_assoc_sentence_neural_desktop = tbl["association"]["sentence_neural_desktop"].value_or(false);
         g_assoc_sentence_neural_keyboard = tbl["association"]["sentence_neural_keyboard"].value_or(true);
         g_assoc_sentence_show_next_on_duplicate = tbl["association"]["sentence_show_next_on_duplicate"].value_or(false);
+        g_assoc_sentence_collocation_additive = tbl["association"]["sentence_collocation_additive"].value_or(false);
+        g_assoc_sentence_collocation_rerank = tbl["association"]["sentence_collocation_rerank"].value_or(false);
+        g_assoc_sentence_collocation_model = tbl["association"]["sentence_collocation_model"].value_or(std::string());
+        g_assoc_sentence_collocation_weight = tbl["association"]["sentence_collocation_weight"].value_or(0.1);
+        g_assoc_sentence_collocation_rerank_weight =
+            tbl["association"]["sentence_collocation_rerank_weight"].value_or(0.05);
         g_assoc_sentence_source_badge = tbl["association"]["sentence_source_badge"].value_or(false);
         g_emoji_mixed_input_enabled = tbl["general"]["emoji_mixed_input"].value_or(false);
         g_kaomoji_mixed_input_enabled = tbl["general"]["kaomoji_mixed_input"].value_or(false);

server/src/config/ime_config.h

@@ -361,6 +361,15 @@ bool GetConfiguredAssocSentenceShowNextOnDuplicate();
 bool SetConfiguredAssocSentenceShowNextOnDuplicate(bool enabled);
 bool GetConfiguredAssocSentenceSourceBadge();
 bool SetConfiguredAssocSentenceSourceBadge(bool enabled);
+// 万象语法模型（[association] 段）：两个机制开关进设置页，模型 id 由下载器写回，
+// 权重是配置文件里的高级调参项，不进设置页。
+bool GetConfiguredAssocSentenceCollocationAdditive();
+bool SetConfiguredAssocSentenceCollocationAdditive(bool enabled);
+bool GetConfiguredAssocSentenceCollocationRerank();
+bool SetConfiguredAssocSentenceCollocationRerank(bool enabled);
+bool GetConfiguredAssocSentenceCollocationRerankWeight();
+std::string GetConfiguredAssocSentenceCollocationModel();
+double GetConfiguredAssocSentenceCollocationWeight();
 bool GetConfiguredUnicodeModeEnabled();
 bool SetConfiguredUnicodeModeEnabled(bool enabled);
 // Shift+K 快捷短语模式。

server/src/config/ime_config_general.cpp

@@ -208,6 +208,49 @@ bool SetConfiguredAssocSentenceNeuralKeyboard(bool enabled)
     return true;
 }
 
+bool GetConfiguredAssocSentenceCollocationAdditive()
+{
+    return g_assoc_sentence_collocation_additive;
+}
+bool SetConfiguredAssocSentenceCollocationAdditive(bool enabled)
+{
+    if (!WriteConfiguredValue("association", "sentence_collocation_additive", enabled ? "true" : "false"))
+    {
+        return false;
+    }
+    g_assoc_sentence_collocation_additive = enabled;
+    return true;
+}
+
+bool GetConfiguredAssocSentenceCollocationRerank()
+{
+    return g_assoc_sentence_collocation_rerank;
+}
+bool SetConfiguredAssocSentenceCollocationRerank(bool enabled)
+{
+    if (!WriteConfiguredValue("association", "sentence_collocation_rerank", enabled ? "true" : "false"))
+    {
+        return false;
+    }
+    g_assoc_sentence_collocation_rerank = enabled;
+    return true;
+}
+
+bool GetConfiguredAssocSentenceCollocationRerankWeight()
+{
+    return g_assoc_sentence_collocation_rerank_weight;
+}
+
+std::string GetConfiguredAssocSentenceCollocationModel()
+{
+    return g_assoc_sentence_collocation_model;
+}
+
+double GetConfiguredAssocSentenceCollocationWeight()
+{
+    return g_assoc_sentence_collocation_weight;
+}
+
 bool GetConfiguredAssocSentenceShowNextOnDuplicate()
 {
     return g_assoc_sentence_show_next_on_duplicate;

server/src/config/ime_config_internal.h

@@ -164,6 +164,11 @@ extern bool g_assoc_sentence_neural_desktop;
 extern bool g_assoc_sentence_neural_keyboard;
 extern bool g_assoc_sentence_show_next_on_duplicate;
 extern bool g_assoc_sentence_source_badge;
+extern bool g_assoc_sentence_collocation_additive;
+extern bool g_assoc_sentence_collocation_rerank;
+extern std::string g_assoc_sentence_collocation_model;
+extern double g_assoc_sentence_collocation_weight;
+extern double g_assoc_sentence_collocation_rerank_weight;
 extern bool g_emoji_mixed_input_enabled;
 extern bool g_kaomoji_mixed_input_enabled;
 extern bool g_unicode_mode_enabled;

server/src/ipc/candidate_selection_policy.h

@@ -31,12 +31,14 @@ inline size_t CountCanonicalSyllables(const std::string &canonical_pinyin) noexc
     return 1 + static_cast<size_t>(std::count(canonical_pinyin.begin(), canonical_pinyin.end(), '\''));
 }
 
-// 猜出来的整句来源：词格 Generated、Google 解码器 Fallback，以及神经整句
-// NeuralDesktop / NeuralKeyboard。它们都不是词库里已有的行，落库/学习判定同类处理。
+// 猜出来的整句来源：词格 Generated、Google 解码器 Fallback，神经整句
+// NeuralDesktop / NeuralKeyboard，以及万象语法模型重排的 Collocation。
+// 它们都不是词库里已有的行，落库/学习判定同类处理。
 constexpr bool IsGuessedSentenceSource(CandidateSource source) noexcept
 {
     return source == CandidateSource::Generated || source == CandidateSource::Fallback ||
-           source == CandidateSource::NeuralDesktop || source == CandidateSource::NeuralKeyboard;
+           source == CandidateSource::NeuralDesktop || source == CandidateSource::NeuralKeyboard ||
+           source == CandidateSource::Collocation;
 }
 
 // 整句候选独立上屏——不接在造词前缀后面、自己就是整条输入——时是否该落库。该落：整句是
@@ -64,10 +66,11 @@ inline bool ShouldStoreEarlyReturnPhrase(CandidateSource source, bool creating_w
                                          const std::string &prefix_canonical_pinyin,
                                          const std::string &candidate_canonical_pinyin) noexcept
 {
-    // 与词格 Generated 同一支：神经整句同样带 canonical quanpin，可以结束一段造词或独立
-    // 上屏。Google Fallback 沿用旧语义仍不走这条造词落库路径。
+    // 与词格 Generated 同一支：神经整句与万象重排句同样带 canonical quanpin，可以结束
+    // 一段造词或独立上屏。Google Fallback 沿用旧语义仍不走这条造词落库路径。
     const bool early_return_source = source == CandidateSource::Generated || source == CandidateSource::NeuralDesktop ||
-                                     source == CandidateSource::NeuralKeyboard;
+                                     source == CandidateSource::NeuralKeyboard ||
+                                     source == CandidateSource::Collocation;
     if (!early_return_source || candidate_canonical_pinyin.empty())
     {
         return false;

server/src/ipc/event_listener_candidates.cpp

@@ -302,6 +302,8 @@ std::string BuildCurrentCandidatePage()
                 view.badge = " 〔神经D〕";
             else if (item.source == CandidateSource::NeuralKeyboard)
                 view.badge = " 〔神经K〕";
+            else if (item.source == CandidateSource::Collocation)
+                view.badge = " 〔万象〕";
         }
         view.fixed_position = item.fixed_position > 0;
         ApplyFixedPositionBadge(view, show_fixed_badge, fixed_badge_style);

server/src/session/engine_input_session.cpp

@@ -4,6 +4,30 @@
 #include "engine/core/sentence_association_options.h"
 #include "engine/quanpin/quanpin_utils.h"
 
+#include <filesystem>
+
+namespace
+{
+// 模型包的确定性布局：<resources>/models/<id>/<id>.gram。下载器与手动放置都
+// 遵守它，解析因此只是一次 stat，不需要目录扫描，也不需要 model.toml。
+std::string ResolveCollocationModelPath(const std::string &model_id)
+{
+    if (model_id.empty())
+    {
+        return {};
+    }
+    // 会话持有的是 legacy() 布局：资源根就是数据根，模型包随安装数据走。
+    const std::filesystem::path file =
+        metasequoia::RuntimePaths::legacy().resources / "models" / model_id / (model_id + ".gram");
+    std::error_code error;
+    if (!std::filesystem::is_regular_file(file, error) || error)
+    {
+        return {};
+    }
+    return file.u8string();
+}
+} // namespace
+
 EngineInputSession::EngineInputSession(SchemeType scheme, const ShuangpinProfile &profile)
     : paths_(metasequoia::RuntimePaths::legacy()), session_(scheme, profile, paths_)
 {
@@ -47,6 +71,18 @@ void EngineInputSession::ApplyConfiguration()
     association.neural_desktop = GetConfiguredAssocSentenceNeuralDesktop();
     association.neural_keyboard = GetConfiguredAssocSentenceNeuralKeyboard();
     association.show_next_on_duplicate = GetConfiguredAssocSentenceShowNextOnDuplicate();
+    // 万象语法模型：两个机制共用一份模型包。模型 id 按 <resources>/models/<id>/<id>.gram
+    // 解析成路径（下载器与手动放置都遵守这个命名）；开关开着但文件不在就等于关，词格
+    // 静默降级。解析是一次 stat，按键路径上可忽略。
+    association.collocation_model = ResolveCollocationModelPath(GetConfiguredAssocSentenceCollocationModel());
+    association.collocation_weight = GetConfiguredAssocSentenceCollocationWeight();
+    association.collocation_rerank = GetConfiguredAssocSentenceCollocationRerank();
+    association.collocation_rerank_weight = GetConfiguredAssocSentenceCollocationRerankWeight();
+    if (association.collocation_model.empty())
+    {
+        // 模型缺席时连开关一起置空，避免词典层拿空路径做无谓解析。
+        association.collocation_rerank = false;
+    }
     session_.set_sentence_association(association);
     session_.set_shuangpin_preedit_uses_raw(GetConfiguredShuangpinPreeditMode() == "shuangpin");
     // 五笔拼音混输与 z 键角色是两个独立设置：混输是「同时给五笔和拼音候选」，z 键角色只管

server/src/settings/collocation_model.cpp

@@ -0,0 +1,292 @@
+#include "collocation_model.h"
+
+#include "engine/core/data_path.h"
+
+#include <Windows.h>
+#include <bcrypt.h>
+#include <winhttp.h>
+
+#include <atomic>
+#include <filesystem>
+#include <fstream>
+#include <mutex>
+#include <sstream>
+#include <string>
+#include <thread>
+#include <vector>
+
+#pragma comment(lib, "winhttp.lib")
+#pragma comment(lib, "bcrypt.lib")
+
+namespace collocation
+{
+namespace
+{
+
+// 模型包的钉死输入。bytes 与 sha256 来自
+// https://github.com/amzxyz/RIME-LMDG/releases/tag/LTS 的资产清单，
+// 与 docs/research/2026-10-01-wanxiang-octagram-model.md 的评测基线同一份字节。
+constexpr const wchar_t *kModelHost = L"github.com";
+constexpr const wchar_t *kModelPath = L"/amzxyz/RIME-LMDG/releases/download/LTS/wanxiang-lts-zh-hans.gram";
+constexpr const char *kModelSha256 = "ae43724a9aa02b4c493c603025549d2cba6fa6a67ae3ae040e55efdfeeaa1183";
+constexpr long long kModelBytes = 409719852LL;
+constexpr const char *kModelId = "wanxiang-lts-zh-hans";
+
+std::filesystem::path ModelDirectory()
+{
+    return metasequoia::data_directory() / "models" / kModelId;
+}
+
+std::filesystem::path ModelFile()
+{
+    return ModelDirectory() / (std::string(kModelId) + ".gram");
+}
+
+std::filesystem::path PartFile()
+{
+    // 同一卷上的临时名，下载完成后原子 rename 到位。
+    return metasequoia::data_directory() / "models" / (std::string(kModelId) + ".gram.part");
+}
+
+std::string Sha256Hex(const std::filesystem::path &file)
+{
+    BCRYPT_ALG_HANDLE algorithm = nullptr;
+    BCRYPT_HASH_HANDLE hash = nullptr;
+    std::string result;
+    DWORD digest_length = 0, object_length = 0, callback = 0;
+    if (BCryptOpenAlgorithmProvider(&algorithm, BCRYPT_SHA256_ALGORITHM, nullptr, 0) != 0 ||
+        BCryptGetProperty(algorithm, BCRYPT_HASH_LENGTH, reinterpret_cast<PUCHAR>(&digest_length),
+                          sizeof(digest_length), &callback, 0) != 0 ||
+        BCryptGetProperty(algorithm, BCRYPT_OBJECT_LENGTH, reinterpret_cast<PUCHAR>(&object_length),
+                          sizeof(object_length), &callback, 0) != 0)
+    {
+        if (algorithm)
+            BCryptCloseAlgorithmProvider(algorithm, 0);
+        return {};
+    }
+    std::vector<unsigned char> hash_object(object_length);
+    if (BCryptCreateHash(algorithm, &hash, hash_object.data(), object_length, nullptr, 0, 0) == 0)
+    {
+        std::ifstream in(file, std::ios::binary);
+        std::vector<char> buffer(1 << 20);
+        bool ok = static_cast<bool>(in);
+        while (ok && in)
+        {
+            in.read(buffer.data(), static_cast<std::streamsize>(buffer.size()));
+            const auto read = in.gcount();
+            if (read > 0)
+                ok = BCryptHashData(hash, reinterpret_cast<PUCHAR>(buffer.data()), static_cast<ULONG>(read), 0) == 0;
+        }
+        if (ok)
+        {
+            std::vector<unsigned char> digest(digest_length);
+            ok = BCryptFinishHash(hash, digest.data(), digest_length, 0) == 0;
+            static const char *kHex = "0123456789abcdef";
+            for (unsigned char byte : digest)
+            {
+                result.push_back(kHex[byte >> 4]);
+                result.push_back(kHex[byte & 0x0F]);
+            }
+        }
+        BCryptDestroyHash(hash);
+    }
+    BCryptCloseAlgorithmProvider(algorithm, 0);
+    return result;
+}
+
+enum class DownloadState
+{
+    Idle,
+    Downloading,
+    Error,
+};
+
+std::mutex g_mutex;
+DownloadState g_state = DownloadState::Idle;
+int g_progress = 0;
+std::string g_error;
+
+void SetState(DownloadState state, int progress, std::string error)
+{
+    std::lock_guard lock(g_mutex);
+    g_state = state;
+    g_progress = progress;
+    g_error = std::move(error);
+}
+
+// 后台线程：下载 -> 校验 -> 原子落位。全程只碰 PartFile，失败时不留半个模型
+// 在正式位置上。GitHub 的 release 资产经 302 跳转到 CDN，显式放开自动重定向。
+void DownloadThread()
+{
+    SetState(DownloadState::Downloading, 0, {});
+
+    std::error_code fs_error;
+    const std::filesystem::path directory = ModelDirectory();
+    std::filesystem::create_directories(directory, fs_error);
+    if (fs_error)
+    {
+        SetState(DownloadState::Error, 0, "无法创建模型目录");
+        return;
+    }
+
+    HINTERNET session = WinHttpOpen(L"MetasequoiaImeServer/1.0", WINHTTP_ACCESS_TYPE_DEFAULT_PROXY,
+                                    WINHTTP_NO_PROXY_NAME, WINHTTP_NO_PROXY_BYPASS, 0);
+    if (session == nullptr)
+    {
+        SetState(DownloadState::Error, 0, "无法初始化网络");
+        return;
+    }
+    // 400MB 不是快操作：连接阶段给足超时，收发阶段不设上限靠进度与失败兜底。
+    WinHttpSetTimeouts(session, 30000, 30000, 30000, 0);
+    HINTERNET connection = WinHttpConnect(session, kModelHost, INTERNET_DEFAULT_HTTPS_PORT, 0);
+    HINTERNET request = nullptr;
+    if (connection != nullptr)
+    {
+        request = WinHttpOpenRequest(connection, L"GET", kModelPath, nullptr, WINHTTP_NO_REFERER,
+                                     WINHTTP_DEFAULT_ACCEPT_TYPES, WINHTTP_FLAG_SECURE);
+        if (request != nullptr)
+        {
+            DWORD policy = WINHTTP_OPTION_REDIRECT_POLICY_ALWAYS;
+            WinHttpSetOption(request, WINHTTP_OPTION_REDIRECT_POLICY, &policy, sizeof(policy));
+        }
+    }
+    bool ok = connection != nullptr && request != nullptr &&
+              WinHttpSendRequest(request, WINHTTP_NO_ADDITIONAL_HEADERS, 0, WINHTTP_NO_REQUEST_DATA, 0, 0, 0) &&
+              WinHttpReceiveResponse(request, nullptr);
+    DWORD status = 0;
+    DWORD status_size = sizeof(status);
+    if (ok)
+    {
+        WinHttpQueryHeaders(request, WINHTTP_QUERY_STATUS_CODE | WINHTTP_QUERY_FLAG_NUMBER,
+                            WINHTTP_HEADER_NAME_BY_INDEX, &status, &status_size, WINHTTP_NO_HEADER_INDEX);
+        ok = status == HTTP_STATUS_OK;
+    }
+
+    std::ofstream out;
+    if (ok)
+    {
+        out.open(PartFile(), std::ios::binary | std::ios::trunc);
+        ok = static_cast<bool>(out);
+    }
+
+    long long received = 0;
+    while (ok)
+    {
+        DWORD available = 0;
+        if (!WinHttpQueryDataAvailable(request, &available))
+        {
+            ok = false;
+            break;
+        }
+        if (available == 0)
+            break;
+        std::vector<char> buffer(available);
+        DWORD read = 0;
+        if (!WinHttpReadData(request, buffer.data(), available, &read) || read == 0)
+        {
+            ok = false;
+            break;
+        }
+        out.write(buffer.data(), static_cast<std::streamsize>(read));
+        if (!out)
+        {
+            ok = false;
+            break;
+        }
+        received += read;
+        const long long total = kModelBytes;
+        if (total > 0)
+        {
+            const int progress = static_cast<int>((std::min)(100LL, received * 100LL / total));
+            SetState(DownloadState::Downloading, progress, {});
+        }
+    }
+    if (request != nullptr)
+        WinHttpCloseHandle(request);
+    if (connection != nullptr)
+        WinHttpCloseHandle(connection);
+    WinHttpCloseHandle(session);
+    out.close();
+
+    if (!ok)
+    {
+        SetState(DownloadState::Error, 0, status != 0 && status != HTTP_STATUS_OK ? "下载响应异常" : "下载中断");
+        std::error_code cleanup;
+        std::filesystem::remove(PartFile(), cleanup);
+        return;
+    }
+
+    // 字节级校验：LTS tag 会被上游原地重传，这一步是防漂移的唯一闸门。
+    if (std::filesystem::file_size(PartFile()) != static_cast<unsigned long long>(kModelBytes))
+    {
+        SetState(DownloadState::Error, 0, "下载字节数与锁定值不符");
+        std::error_code cleanup;
+        std::filesystem::remove(PartFile(), cleanup);
+        return;
+    }
+    const std::string digest = Sha256Hex(PartFile());
+    if (digest != kModelSha256)
+    {
+        SetState(DownloadState::Error, 0, "SHA256 与锁定值不符，模型可能已被上游更换");
+        std::error_code cleanup;
+        std::filesystem::remove(PartFile(), cleanup);
+        return;
+    }
+
+    std::filesystem::rename(PartFile(), ModelFile(), fs_error);
+    if (fs_error)
+    {
+        SetState(DownloadState::Error, 0, "模型落位失败");
+        return;
+    }
+
+    // CC-BY-4.0 的署名义务随模型走：NOTICE 与模型同目录，注明来源与锁定摘要。
+    std::ofstream notice(ModelDirectory() / "NOTICE.md", std::ios::binary | std::ios::trunc);
+    if (notice)
+    {
+        notice << "# 万象语法模型（" << kModelId << "）\n\n"
+               << "- 来源：" << "https://github.com/amzxyz/RIME-LMDG/releases/tag/LTS\n"
+               << "- 许可：CC-BY-4.0（© amzxyz / RIME-LMDG 项目）\n"
+               << "- 文件：" << kModelId << ".gram（" << kModelBytes << " 字节）\n"
+               << "- SHA256：" << kModelSha256 << "\n";
+    }
+    SetState(DownloadState::Idle, 100, {});
+}
+
+} // namespace
+
+ModelStatus GetModelStatus()
+{
+    std::error_code fs_error;
+    if (std::filesystem::exists(ModelFile(), fs_error) && !fs_error &&
+        static_cast<long long>(std::filesystem::file_size(ModelFile(), fs_error)) == kModelBytes && !fs_error)
+    {
+        return {"ready", 100, {}};
+    }
+    std::lock_guard lock(g_mutex);
+    switch (g_state)
+    {
+    case DownloadState::Downloading:
+        return {"downloading", g_progress, {}};
+    case DownloadState::Error:
+        return {"error", 0, g_error};
+    default:
+        return {"absent", 0, {}};
+    }
+}
+
+bool StartDownload()
+{
+    {
+        std::lock_guard lock(g_mutex);
+        if (g_state == DownloadState::Downloading)
+            return true;
+        g_state = DownloadState::Downloading;
+        g_progress = 0;
+        g_error.clear();
+    }
+    std::thread(DownloadThread).detach();
+    return true;
+}
+
+} // namespace collocation

server/src/settings/collocation_model.h

@@ -0,0 +1,33 @@
+#pragma once
+
+// 万象语法模型（octagram .gram）的按需下载与状态查询。
+//
+// 390MB 的模型不进安装包：设置页提供下载按钮，落到
+// <DataDir>/models/wanxiang-lts-zh-hans/wanxiang-lts-zh-hans.gram，
+// SHA256 与字节数在本文件钉死。上游 LTS release 会被原地重传（tag 不变、字节变），
+// 所以这里的摘要就是防漂移的锁；上游更新模型时必须显式改这里的常量并复跑
+// docs/research 的离线评测，而不是让旧字节静默失效。
+//
+// 状态以磁盘为准（存在且字节数吻合 = ready），下载态是各进程内存里的
+// runtime 状态：独立设置进程与 Server 各自能看到自己的下载进度。
+
+#include <string>
+
+namespace collocation
+{
+
+struct ModelStatus
+{
+    std::string state; // "absent" | "downloading" | "ready" | "error"
+    int progress = 0;  // 下载中 0-100；其余状态无意义
+    std::string error; // state == "error" 时的人类可读原因
+};
+
+// 磁盘现状 + 本进程下载态。轻量，可随配置快照频繁调用。
+ModelStatus GetModelStatus();
+
+// 幂等启动后台下载：已在下载或已就绪时返回 true 不重复启动；磁盘空间不足、
+// 无法创建目录等同步失败返回 false 并把原因记入状态。完成/失败经状态查询可见。
+bool StartDownload();
+
+} // namespace collocation

server/src/settings/settings_app.cpp

@@ -5,6 +5,7 @@
 #include "resource/resource.h"
 #include "settings/settings_launcher.h"
 #include "settings/api_credential_test.h"
+#include "settings/collocation_model.h"
 #include "settings/settings_splash.h"
 #include "settings/dictionary_manager.h"
 #include "settings/serial_task_queue.h"
@@ -506,7 +507,13 @@ std::wstring BuildConfigMessage(bool refresh_skin_catalog)
             {"sentence_neural_desktop", GetConfiguredAssocSentenceNeuralDesktop()},
             {"sentence_neural_keyboard", GetConfiguredAssocSentenceNeuralKeyboard()},
             {"sentence_show_next_on_duplicate", GetConfiguredAssocSentenceShowNextOnDuplicate()},
-            {"sentence_source_badge", GetConfiguredAssocSentenceSourceBadge()}}},
+            {"sentence_source_badge", GetConfiguredAssocSentenceSourceBadge()},
+            {"sentence_collocation_additive", GetConfiguredAssocSentenceCollocationAdditive()},
+            {"sentence_collocation_rerank", GetConfiguredAssocSentenceCollocationRerank()},
+            {"sentence_collocation_model_status", [] {
+                 const auto status = collocation::GetModelStatus();
+                 return nlohmann::json{{"state", status.state}, {"progress", status.progress}, {"error", status.error}};
+             }()}}},
           {"keybindings",
            {{"switch_language_shift", GetConfiguredSwitchLanguageShiftEnabled()},
             {"switch_language_ctrl", GetConfiguredSwitchLanguageCtrlEnabled()},
@@ -880,6 +887,10 @@ bool ApplyConfigUpdate(const json::object &data)
         return SetConfiguredAssocSentenceShowNextOnDuplicate(json::value_to<bool>(data.at("value")));
     if (path == "association.sentence_source_badge")
         return SetConfiguredAssocSentenceSourceBadge(json::value_to<bool>(data.at("value")));
+    if (path == "association.sentence_collocation_additive")
+        return SetConfiguredAssocSentenceCollocationAdditive(json::value_to<bool>(data.at("value")));
+    if (path == "association.sentence_collocation_rerank")
+        return SetConfiguredAssocSentenceCollocationRerank(json::value_to<bool>(data.at("value")));
     if (path == "utility.unicode_mode")
         return SetConfiguredUnicodeModeEnabled(json::value_to<bool>(data.at("value")));
     if (path == "utility.quick_phrase")
@@ -1327,6 +1338,16 @@ void HandleWebMessage(HWND hwnd, ICoreWebView2WebMessageReceivedEventArgs *args)
             if (!ec)
                 ShellExecuteW(hwnd, L"open", directory.c_str(), nullptr, nullptr, SW_SHOWNORMAL);
         }
+        else if (type == "collocationModelDownload")
+        {
+            // 后台线程下载，进度随下一次配置快照回给页面；页面在下载态轮询 configRequest。
+            collocation::StartDownload();
+            PostConfig(false);
+        }
+        else if (type == "collocationModelStatusRequest")
+        {
+            PostConfig(false);
+        }
         else if (type == "configUpdate")
         {
             const auto data = value.at("data").as_object();

server/src/webview2/windows_webview2_settings.cpp

@@ -10,6 +10,7 @@
 #include "ipc/ipc.h"
 #include "ipc/event_listener.h"
 #include "skin/candidate_skin_catalog.h"
+#include "settings/collocation_model.h"
 #include "utils/common_utils.h"
 #include <dwmapi.h>
 #include <nlohmann/json.hpp>
@@ -375,6 +376,16 @@ HRESULT OnControllerCreatedSettingsWnd(            //
                         if (!ec)
                             ShellExecuteW(hwnd, L"open", directory.c_str(), nullptr, nullptr, SW_SHOWNORMAL);
                     }
+                    else if (type == "collocationModelDownload")
+                    {
+                        // 后台线程下载，进度随下一次配置快照回给页面；页面在下载态轮询 configRequest。
+                        collocation::StartDownload();
+                        PostSettingsConfig();
+                    }
+                    else if (type == "collocationModelStatusRequest")
+                    {
+                        PostSettingsConfig();
+                    }
                     else if (type == "configUpdate")
                     {
                         try
@@ -1052,6 +1063,22 @@ HRESULT OnControllerCreatedSettingsWnd(            //
                                     PostSettingsConfig();
                                 }
                             }
+                            else if (path == "association.sentence_collocation_additive")
+                            {
+                                const bool value = json::value_to<bool>(data.at("value"));
+                                if (SetConfiguredAssocSentenceCollocationAdditive(value))
+                                {
+                                    PostSettingsConfig();
+                                }
+                            }
+                            else if (path == "association.sentence_collocation_rerank")
+                            {
+                                const bool value = json::value_to<bool>(data.at("value"));
+                                if (SetConfiguredAssocSentenceCollocationRerank(value))
+                                {
+                                    PostSettingsConfig();
+                                }
+                            }
                             else if (path == "utility.unicode_mode")
                             {
                                 const bool value = json::value_to<bool>(data.at("value"));
@@ -1474,7 +1501,14 @@ void PostSettingsConfig()
             {"sentence_neural_desktop", GetConfiguredAssocSentenceNeuralDesktop()},
             {"sentence_neural_keyboard", GetConfiguredAssocSentenceNeuralKeyboard()},
             {"sentence_show_next_on_duplicate", GetConfiguredAssocSentenceShowNextOnDuplicate()},
-            {"sentence_source_badge", GetConfiguredAssocSentenceSourceBadge()}}},
+            {"sentence_source_badge", GetConfiguredAssocSentenceSourceBadge()},
+            {"sentence_collocation_additive", GetConfiguredAssocSentenceCollocationAdditive()},
+            {"sentence_collocation_rerank", GetConfiguredAssocSentenceCollocationRerank()},
+            {"sentence_collocation_model_status",
+             [] {
+                 const auto status = collocation::GetModelStatus();
+                 return nlohmann::json{{"state", status.state}, {"progress", status.progress}, {"error", status.error}};
+             }()}}},
           {"keybindings",
            {{"switch_language_shift", GetConfiguredSwitchLanguageShiftEnabled()},
             {"switch_language_ctrl", GetConfiguredSwitchLanguageCtrlEnabled()},