From b8372adf5d2f1cddc904572c88dd1d5a14a7c679 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E5=85=AC=E6=98=8E?=
<83812544+Ed1s0nZ@users.noreply.github.com>
Date: Sat, 18 Apr 2026 23:33:48 +0800
Subject: [PATCH] Add files via upload
---
web/static/i18n/en-US.json | 32 +++++++++++++--
web/static/i18n/zh-CN.json | 32 +++++++++++++--
web/static/js/settings.js | 83 +++++++++++++++++++++++++++++---------
web/templates/index.html | 56 +++++++++++++++++++++++--
4 files changed, 176 insertions(+), 27 deletions(-)
diff --git a/web/static/i18n/en-US.json b/web/static/i18n/en-US.json
index a9ecfcbc..698726d7 100644
--- a/web/static/i18n/en-US.json
+++ b/web/static/i18n/en-US.json
@@ -1299,10 +1299,36 @@
"similarityThreshold": "Similarity threshold",
"similarityPlaceholder": "0.7",
"similarityHint": "Results below this value are filtered (0-1)",
- "hybridWeight": "Hybrid weight",
- "hybridPlaceholder": "0.7",
- "hybridHint": "Vector weight (0-1); 1.0 = vector only, 0.0 = keyword only",
+ "subIndexFilter": "Sub-index filter (optional)",
+ "subIndexFilterPlaceholder": "e.g. prod, must match an indexing sub_indexes tag",
+ "subIndexFilterHint": "Empty = no filter. When set, only rows whose sub_indexes contain this tag (legacy rows with empty sub_indexes still match).",
+ "postRetrieveHeader": "Post-retrieval (dedupe / budget)",
+ "postRetrieveDedupeAuto": "Results are always deduped by normalized text (whitespace-collapsed bodies). No setting required.",
+ "prefetchTopK": "Prefetch candidates (vector stage)",
+ "prefetchTopKPlaceholder": "0",
+ "prefetchTopKHint": "0 = same as Top-K; larger values fetch more vector hits before dedupe/truncate (max 200).",
+ "maxContextChars": "Max returned characters (Unicode)",
+ "maxContextCharsPlaceholder": "0",
+ "maxContextCharsHint": "0 = unlimited; keeps whole chunks in rank order until the budget is exceeded.",
+ "maxContextTokens": "Max returned tokens",
+ "maxContextTokensPlaceholder": "0",
+ "maxContextTokensHint": "0 = unlimited; tiktoken estimate (embedding model name, fallback cl100k_base).",
"indexConfig": "Index config",
+ "chunkStrategy": "Chunking strategy",
+ "chunkStrategyMarkdownRecursive": "Markdown headers, then recursive (recommended)",
+ "chunkStrategyRecursive": "Recursive only",
+ "chunkStrategyHint": "Matches Eino-style pipelines: Markdown headers + recursive for docs; plain text can use recursive only.",
+ "requestTimeoutSeconds": "Embedding HTTP timeout (seconds)",
+ "requestTimeoutPlaceholder": "120",
+ "requestTimeoutHint": "0 uses the default 120s embedding HTTP client timeout.",
+ "batchSize": "Embedding batch size",
+ "batchSizePlaceholder": "64",
+ "batchSizeHint": "Max texts per embedding request (SQLite indexer batches writes accordingly).",
+ "preferSourceFile": "Prefer on-disk source file when indexing (Eino FileLoader)",
+ "preferSourceFileHint": "When enabled, content comes from file_path; falls back to DB content if load fails.",
+ "subIndexes": "Eino sub-indexes (comma-separated)",
+ "subIndexesPlaceholder": "e.g. prod, knowledge",
+ "subIndexesHint": "Passed to indexer.WithSubIndexes; stored in the sub_indexes column.",
"chunkSize": "Chunk size",
"chunkSizePlaceholder": "512",
"chunkSizeHint": "Max tokens per chunk (default 512)",
diff --git a/web/static/i18n/zh-CN.json b/web/static/i18n/zh-CN.json
index 9b8679da..fcbc6d5b 100644
--- a/web/static/i18n/zh-CN.json
+++ b/web/static/i18n/zh-CN.json
@@ -1299,10 +1299,36 @@
"similarityThreshold": "相似度阈值",
"similarityPlaceholder": "0.7",
"similarityHint": "相似度阈值（0-1），低于此值的结果将被过滤",
- "hybridWeight": "混合检索权重",
- "hybridPlaceholder": "0.7",
- "hybridHint": "向量检索的权重（0-1），1.0表示纯向量检索，0.0表示纯关键词检索",
+ "subIndexFilter": "子索引过滤（可选）",
+ "subIndexFilterPlaceholder": "如 prod，与索引 sub_indexes 一致",
+ "subIndexFilterHint": "留空不过滤；填写后仅检索向量行 sub_indexes 中含该标签的结果（未打标旧行仍保留）。",
+ "postRetrieveHeader": "检索后处理（去重 / 预算）",
+ "postRetrieveDedupeAuto": "检索结果会自动按正文规范化去重（合并仅空白不同的重复片段），无需配置。",
+ "prefetchTopK": "预取候选数（向量阶段）",
+ "prefetchTopKPlaceholder": "0",
+ "prefetchTopKHint": "0 表示与 Top-K 相同；大于 Top-K 时先多取候选再经去重/截断回到 Top-K（上限 200）。",
+ "maxContextChars": "返回内容最大字符数（Unicode）",
+ "maxContextCharsPlaceholder": "0",
+ "maxContextCharsHint": "0 表示不限制；按检索顺序整段保留 chunk，超出则丢弃后续。",
+ "maxContextTokens": "返回内容最大 Token 数",
+ "maxContextTokensPlaceholder": "0",
+ "maxContextTokensHint": "0 表示不限制；tiktoken 估算（与嵌入模型名一致，失败则用 cl100k_base）。",
"indexConfig": "索引配置",
+ "chunkStrategy": "分块策略",
+ "chunkStrategyMarkdownRecursive": "Markdown 标题切分后递归（推荐）",
+ "chunkStrategyRecursive": "仅递归切分",
+ "chunkStrategyHint": "与 Eino 索引链一致：技术文档建议 Markdown 标题 + 递归；纯文本可仅用递归。",
+ "requestTimeoutSeconds": "嵌入 HTTP 超时（秒）",
+ "requestTimeoutPlaceholder": "120",
+ "requestTimeoutHint": "0 表示使用默认 120 秒，与嵌入 HTTP 客户端一致。",
+ "batchSize": "嵌入批大小",
+ "batchSizePlaceholder": "64",
+ "batchSizeHint": "单次嵌入请求的文本条数上限（SQLite 写入按此分批）。",
+ "preferSourceFile": "索引时优先从磁盘源文件读取（Eino FileLoader）",
+ "preferSourceFileHint": "开启后以 file_path 为准；读取失败时回退数据库中的 content。",
+ "subIndexes": "Eino 子索引（逗号分隔）",
+ "subIndexesPlaceholder": "例如: prod, knowledge",
+ "subIndexesHint": "对应 indexer.WithSubIndexes，持久化到向量表 sub_indexes 字段。",
"chunkSize": "分块大小（Chunk Size）",
"chunkSizePlaceholder": "512",
"chunkSizeHint": "每个块的最大 token 数（默认 512），长文本会被分割成多个块",
diff --git a/web/static/js/settings.js b/web/static/js/settings.js
index 0428b9da..38eee1f6 100644
--- a/web/static/js/settings.js
+++ b/web/static/js/settings.js
@@ -182,15 +182,49 @@ async function loadConfig(loadTools = true) {
retrievalThresholdInput.value = knowledge.retrieval?.similarity_threshold || 0.7;
}
- const retrievalWeightInput = document.getElementById('knowledge-retrieval-hybrid-weight');
- if (retrievalWeightInput) {
- const hybridWeight = knowledge.retrieval?.hybrid_weight;
- // 允许0.0值，只有undefined/null时才使用默认值
- retrievalWeightInput.value = (hybridWeight !== undefined && hybridWeight !== null) ? hybridWeight : 0.7;
+ const subIdxFilterInput = document.getElementById('knowledge-retrieval-sub-index-filter');
+ if (subIdxFilterInput) {
+ subIdxFilterInput.value = knowledge.retrieval?.sub_index_filter || '';
+ }
+
+ const post = knowledge.retrieval?.post_retrieve || {};
+ const prefetchInput = document.getElementById('knowledge-post-retrieve-prefetch-top-k');
+ if (prefetchInput) {
+ prefetchInput.value = post.prefetch_top_k ?? 0;
+ }
+ const maxCharsInput = document.getElementById('knowledge-post-retrieve-max-chars');
+ if (maxCharsInput) {
+ maxCharsInput.value = post.max_context_chars ?? 0;
+ }
+ const maxTokInput = document.getElementById('knowledge-post-retrieve-max-tokens');
+ if (maxTokInput) {
+ maxTokInput.value = post.max_context_tokens ?? 0;
}
// 索引配置
const indexing = knowledge.indexing || {};
+ const chunkStrategySelect = document.getElementById('knowledge-indexing-chunk-strategy');
+ if (chunkStrategySelect) {
+ const v = (indexing.chunk_strategy || 'markdown_then_recursive').toLowerCase();
+ chunkStrategySelect.value = v === 'recursive' ? 'recursive' : 'markdown_then_recursive';
+ }
+ const reqTimeoutInput = document.getElementById('knowledge-indexing-request-timeout');
+ if (reqTimeoutInput) {
+ reqTimeoutInput.value = indexing.request_timeout_seconds ?? 120;
+ }
+ const batchSizeInput = document.getElementById('knowledge-indexing-batch-size');
+ if (batchSizeInput) {
+ batchSizeInput.value = indexing.batch_size ?? 64;
+ }
+ const preferFileCb = document.getElementById('knowledge-indexing-prefer-source-file');
+ if (preferFileCb) {
+ preferFileCb.checked = indexing.prefer_source_file === true;
+ }
+ const subIdxInput = document.getElementById('knowledge-indexing-sub-indexes');
+ if (subIdxInput) {
+ const arr = indexing.sub_indexes;
+ subIdxInput.value = Array.isArray(arr) ? arr.join(', ') : (typeof arr === 'string' ? arr : '');
+ }
const chunkSizeInput = document.getElementById('knowledge-indexing-chunk-size');
if (chunkSizeInput) {
chunkSizeInput.value = indexing.chunk_size || 512;
@@ -811,20 +845,33 @@ async function applySettings() {
const val = parseFloat(document.getElementById('knowledge-retrieval-similarity-threshold')?.value);
return isNaN(val) ? 0.7 : val;
})(),
- hybrid_weight: (() => {
- const val = parseFloat(document.getElementById('knowledge-retrieval-hybrid-weight')?.value);
- return isNaN(val) ? 0.7 : val; // 允许0.0值，只有NaN时才使用默认值
- })()
+ sub_index_filter: document.getElementById('knowledge-retrieval-sub-index-filter')?.value?.trim() || '',
+ post_retrieve: {
+ prefetch_top_k: parseInt(document.getElementById('knowledge-post-retrieve-prefetch-top-k')?.value, 10) || 0,
+ max_context_chars: parseInt(document.getElementById('knowledge-post-retrieve-max-chars')?.value, 10) || 0,
+ max_context_tokens: parseInt(document.getElementById('knowledge-post-retrieve-max-tokens')?.value, 10) || 0
+ }
},
- indexing: {
- chunk_size: parseInt(document.getElementById("knowledge-indexing-chunk-size")?.value) || 512,
- chunk_overlap: parseInt(document.getElementById("knowledge-indexing-chunk-overlap")?.value) ?? 50,
- max_chunks_per_item: parseInt(document.getElementById("knowledge-indexing-max-chunks-per-item")?.value) ?? 0,
- max_rpm: parseInt(document.getElementById("knowledge-indexing-max-rpm")?.value) ?? 0,
- rate_limit_delay_ms: parseInt(document.getElementById("knowledge-indexing-rate-limit-delay-ms")?.value) ?? 300,
- max_retries: parseInt(document.getElementById("knowledge-indexing-max-retries")?.value) ?? 3,
- retry_delay_ms: parseInt(document.getElementById("knowledge-indexing-retry-delay-ms")?.value) ?? 1000
- }
+ indexing: (() => {
+ const subRaw = document.getElementById("knowledge-indexing-sub-indexes")?.value?.trim() || "";
+ const sub_indexes = subRaw
+ ? subRaw.split(/[,，]/).map(s => s.trim()).filter(Boolean)
+ : [];
+ return {
+ chunk_strategy: document.getElementById("knowledge-indexing-chunk-strategy")?.value || "markdown_then_recursive",
+ request_timeout_seconds: parseInt(document.getElementById("knowledge-indexing-request-timeout")?.value, 10) || 0,
+ batch_size: parseInt(document.getElementById("knowledge-indexing-batch-size")?.value, 10) || 0,
+ prefer_source_file: document.getElementById("knowledge-indexing-prefer-source-file")?.checked === true,
+ sub_indexes,
+ chunk_size: parseInt(document.getElementById("knowledge-indexing-chunk-size")?.value) || 512,
+ chunk_overlap: parseInt(document.getElementById("knowledge-indexing-chunk-overlap")?.value) ?? 50,
+ max_chunks_per_item: parseInt(document.getElementById("knowledge-indexing-max-chunks-per-item")?.value) ?? 0,
+ max_rpm: parseInt(document.getElementById("knowledge-indexing-max-rpm")?.value) ?? 0,
+ rate_limit_delay_ms: parseInt(document.getElementById("knowledge-indexing-rate-limit-delay-ms")?.value) ?? 300,
+ max_retries: parseInt(document.getElementById("knowledge-indexing-max-retries")?.value) ?? 3,
+ retry_delay_ms: parseInt(document.getElementById("knowledge-indexing-retry-delay-ms")?.value) ?? 1000
+ };
+ })()
};
const wecomAgentIdVal = document.getElementById('robot-wecom-agent-id')?.value.trim();
diff --git a/web/templates/index.html b/web/templates/index.html
index c1d24ee8..b9785450 100644
--- a/web/templates/index.html
+++ b/web/templates/index.html
@@ -1526,14 +1526,64 @@
相似度阈值（0-1），低于此值的结果将被过滤
-
-
- 向量检索的权重（0-1），1.0表示纯向量检索，0.0表示纯关键词检索
+
+
+ 留空表示不过滤；非空时仅检索 sub_indexes 含该标签的向量行（未打标旧数据仍会命中）。
+
+
+
+ 检索结果会自动按正文规范化去重（合并仅空白不同的重复片段），无需配置。
+
+
+
+ 0 表示与 Top-K 相同；大于 Top-K 时先多取候选再经去重/截断回到 Top-K（上限 200）。
+
+
+
+
+ 0 表示不限制；按检索顺序整段保留 chunk，超出则丢弃后续。
+
+
+
+
+ 0 表示不限制；tiktoken 估算（与嵌入模型名一致，失败则用 cl100k_base）。
+
+
+
+ 与 Eino 官方索引链一致：技术文档建议 Markdown 标题 + 递归；纯文本可仅用递归。
+
+
+
+
+ 0 表示使用默认 120 秒；与 OpenAI 嵌入客户端一致。
+
+
+
+
+ 单次请求嵌入的文本条数上限（SQLite 索引写入分批）。
+
+
+
+ 开启后以 file_path 为准；读取失败时回退数据库中的 content。
+
+
+
+
+ 传入 indexer.WithSubIndexes，写入向量行的 sub_indexes 字段（逻辑分区标记）。
+