diff --git a/.gitignore b/.gitignore
index 844017d54..0275e3f35 100644
--- a/.gitignore
+++ b/.gitignore
@@ -37,6 +37,4 @@ files/helm/fastgpt/charts/*.tgz
 
 tmp/
 coverage
-document/.source
-
-bun.lock
\ No newline at end of file
+document/.source
\ No newline at end of file
diff --git a/document/content/docs/toc.mdx b/document/content/docs/toc.mdx
index 5f6e4505d..5e1659ad9 100644
--- a/document/content/docs/toc.mdx
+++ b/document/content/docs/toc.mdx
@@ -101,6 +101,7 @@ description: FastGPT 文档目录
 - [/docs/upgrading/4-12/4120](/docs/upgrading/4-12/4120)
 - [/docs/upgrading/4-12/4121](/docs/upgrading/4-12/4121)
 - [/docs/upgrading/4-12/4122](/docs/upgrading/4-12/4122)
+- [/docs/upgrading/4-12/4123](/docs/upgrading/4-12/4123)
 - [/docs/upgrading/4-8/40](/docs/upgrading/4-8/40)
 - [/docs/upgrading/4-8/41](/docs/upgrading/4-8/41)
 - [/docs/upgrading/4-8/42](/docs/upgrading/4-8/42)
diff --git a/document/content/docs/upgrading/4-12/4123.mdx b/document/content/docs/upgrading/4-12/4123.mdx
new file mode 100644
index 000000000..60f53c947
--- /dev/null
+++ b/document/content/docs/upgrading/4-12/4123.mdx
@@ -0,0 +1,17 @@
+---
+title: 'V4.12.3(进行中)'
+description: 'FastGPT V4.12.3 更新说明'
+---
+
+  
+## 🚀 新增内容
+
+
+## ⚙️ 优化
+
+1. 纠正 RRF 权重合并算法，使用标准 RRF 权重公式。
+
+## 🐛 修复
+
+
+## 🔨 工具更新
diff --git a/document/content/docs/upgrading/4-12/meta.json b/document/content/docs/upgrading/4-12/meta.json
index fb29138a8..72d8005d2 100644
--- a/document/content/docs/upgrading/4-12/meta.json
+++ b/document/content/docs/upgrading/4-12/meta.json
@@ -1,5 +1,5 @@
 {
   "title": "4.12.x",
   "description": "",
-  "pages": ["4122", "4121", "4120"]
+  "pages": ["4123", "4122", "4121", "4120"]
 }
diff --git a/document/data/doc-last-modified.json b/document/data/doc-last-modified.json
index 02d7a9446..989c6aa02 100644
--- a/document/data/doc-last-modified.json
+++ b/document/data/doc-last-modified.json
@@ -41,7 +41,7 @@
   "document/content/docs/introduction/guide/DialogBoxes/htmlRendering.mdx": "2025-07-23T21:35:03+08:00",
   "document/content/docs/introduction/guide/DialogBoxes/quoteList.mdx": "2025-07-23T21:35:03+08:00",
   "document/content/docs/introduction/guide/admin/sso.mdx": "2025-07-24T13:00:27+08:00",
-  "document/content/docs/introduction/guide/admin/teamMode.mdx": "2025-07-24T13:00:27+08:00",
+  "document/content/docs/introduction/guide/admin/teamMode.mdx": "2025-08-27T16:59:57+08:00",
   "document/content/docs/introduction/guide/course/ai_settings.mdx": "2025-07-24T13:00:27+08:00",
   "document/content/docs/introduction/guide/course/chat_input_guide.mdx": "2025-07-23T21:35:03+08:00",
   "document/content/docs/introduction/guide/course/fileInput.mdx": "2025-07-23T21:35:03+08:00",
@@ -104,7 +104,7 @@
   "document/content/docs/upgrading/4-11/4111.mdx": "2025-08-07T22:49:09+08:00",
   "document/content/docs/upgrading/4-12/4120.mdx": "2025-08-12T22:45:19+08:00",
   "document/content/docs/upgrading/4-12/4121.mdx": "2025-08-15T22:53:06+08:00",
-  "document/content/docs/upgrading/4-12/4122.mdx": "2025-08-26T23:51:54+08:00",
+  "document/content/docs/upgrading/4-12/4122.mdx": "2025-08-27T00:31:33+08:00",
   "document/content/docs/upgrading/4-8/40.mdx": "2025-08-02T19:38:37+08:00",
   "document/content/docs/upgrading/4-8/41.mdx": "2025-08-02T19:38:37+08:00",
   "document/content/docs/upgrading/4-8/42.mdx": "2025-08-02T19:38:37+08:00",
diff --git a/packages/global/core/dataset/search/utils.ts b/packages/global/core/dataset/search/utils.ts
index 52318c837..2fb6383ea 100644
--- a/packages/global/core/dataset/search/utils.ts
+++ b/packages/global/core/dataset/search/utils.ts
@@ -18,7 +18,7 @@ export const datasetSearchResultConcat = (
 
     item.list.forEach((data, index) => {
       const rank = index + 1;
-      const score = (weight * 1) / (60 + rank);
+      const score = weight * (1 / (60 + rank));
       const record = map.get(data.id);
       if (record) {
         // 合并两个score,有相同type的score,取最大值
@@ -64,8 +64,9 @@ export const datasetSearchResultConcat = (
       });
     }
 
-    // @ts-ignore
-    delete item.rrfScore;
-    return item;
+    return {
+      ...item,
+      rrfScore: undefined
+    };
   });
 };
diff --git a/packages/service/core/dataset/search/controller.ts b/packages/service/core/dataset/search/controller.ts
index 8273bafb2..ad29c4de9 100644
--- a/packages/service/core/dataset/search/controller.ts
+++ b/packages/service/core/dataset/search/controller.ts
@@ -849,22 +849,16 @@ export async function searchDatasetData(
     }
   })();
 
-  // embedding recall and fullText recall rrf concat
-  const embWeight = embeddingWeight; // 向量索引的 weight 大小
-  const fullTextWeight = 1 - embeddingWeight; // 全文索引的 weight 大小
-
   const rrfSearchResult = datasetSearchResultConcat([
-    { weight: embWeight, list: embeddingRecallResults },
-    { weight: fullTextWeight, list: fullTextRecallResults }
+    { weight: embeddingWeight, list: embeddingRecallResults },
+    { weight: 1 - embeddingWeight, list: fullTextRecallResults }
   ]);
   const rrfConcatResults = (() => {
     if (reRankResults.length === 0) return rrfSearchResult;
     if (rerankWeight === 1) return reRankResults;
 
-    const searchWeight = 1 - rerankWeight; // 搜索结果的 weight 大小
-
     return datasetSearchResultConcat([
-      { weight: searchWeight, list: rrfSearchResult },
+      { weight: 1 - rerankWeight, list: rrfSearchResult },
       { weight: rerankWeight, list: reRankResults }
     ]);
   })();
diff --git a/test/cases/function/packages/global/core/dataset/search/utils.test.ts b/test/cases/function/packages/global/core/dataset/search/utils.test.ts
new file mode 100644
index 000000000..86743d919
--- /dev/null
+++ b/test/cases/function/packages/global/core/dataset/search/utils.test.ts
@@ -0,0 +1,474 @@
+import { describe, it, expect } from 'vitest';
+import { datasetSearchResultConcat } from '@fastgpt/global/core/dataset/search/utils';
+import { SearchScoreTypeEnum } from '@fastgpt/global/core/dataset/constants';
+import type { SearchDataResponseItemType } from '@fastgpt/global/core/dataset/type';
+
+describe('datasetSearchResultConcat', () => {
+  // Helper function to create test data
+  const createSearchItem = (
+    id: string,
+    q: string,
+    scores: { type: `${SearchScoreTypeEnum}`; value: number; index: number }[] = []
+  ): SearchDataResponseItemType => ({
+    id,
+    datasetId: 'dataset1',
+    collectionId: 'collection1',
+    sourceName: 'source1',
+    sourceId: 'source1',
+    q,
+    a: `Answer for ${q}`,
+    chunkIndex: 0,
+    updateTime: new Date(),
+    score: scores
+  });
+
+  describe('Edge cases', () => {
+    it('should handle empty array', () => {
+      const result = datasetSearchResultConcat([]);
+      expect(result).toEqual([]);
+    });
+
+    it('should handle all empty lists', () => {
+      const input = [
+        { weight: 1.0, list: [] },
+        { weight: 0.5, list: [] }
+      ];
+      const result = datasetSearchResultConcat(input);
+      expect(result).toEqual([]);
+    });
+
+    it('should handle only one non-empty list', () => {
+      const items = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.9, index: 0 }
+        ]),
+        createSearchItem('2', 'Question 2', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.8, index: 1 }
+        ])
+      ];
+
+      const input = [
+        { weight: 1.0, list: items },
+        { weight: 0.5, list: [] }
+      ];
+
+      const result = datasetSearchResultConcat(input);
+      expect(result).toEqual(items);
+    });
+  });
+
+  describe('RRF algorithm tests', () => {
+    it('should calculate RRF scores correctly', () => {
+      const items1 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.9, index: 0 }
+        ]),
+        createSearchItem('2', 'Question 2', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.8, index: 1 }
+        ])
+      ];
+
+      const items2 = [
+        createSearchItem('2', 'Question 2', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.7, index: 0 }
+        ]),
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.6, index: 1 }
+        ])
+      ];
+
+      const input = [
+        { weight: 1.0, list: items1 },
+        { weight: 1.0, list: items2 }
+      ];
+
+      const result = datasetSearchResultConcat(input);
+
+      // Verify RRF score calculation
+      // item1: 1.0 * (1/(60+1)) + 1.0 * (1/(60+2)) = 1/61 + 1/62 ≈ 0.0163934 + 0.0161290 ≈ 0.0325224
+      // item2: 1.0 * (1/(60+2)) + 1.0 * (1/(60+1)) = 1/62 + 1/61 ≈ 0.0161290 + 0.0163934 ≈ 0.0325224
+
+      expect(result).toHaveLength(2);
+
+      // Verify RRF scores are added
+      result.forEach((item) => {
+        const rrfScore = item.score.find((s) => s.type === SearchScoreTypeEnum.rrf);
+        expect(rrfScore).toBeDefined();
+        expect(rrfScore!.value).toBeCloseTo(0.0325224, 6);
+      });
+    });
+
+    it('should weight RRF scores correctly', () => {
+      const items1 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.9, index: 0 }
+        ])
+      ];
+
+      const items2 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.7, index: 0 }
+        ])
+      ];
+
+      const input = [
+        { weight: 2.0, list: items1 }, // Higher weight
+        { weight: 1.0, list: items2 }
+      ];
+
+      const result = datasetSearchResultConcat(input);
+
+      expect(result).toHaveLength(1);
+
+      const rrfScore = result[0].score.find((s) => s.type === SearchScoreTypeEnum.rrf);
+      expect(rrfScore).toBeDefined();
+
+      // Should be: 2.0 * (1/61) + 1.0 * (1/61) = 3.0 * (1/61) ≈ 0.0491803
+      expect(rrfScore!.value).toBeCloseTo(3.0 / 61, 6);
+    });
+  });
+
+  describe('Score merging tests', () => {
+    it('should merge different score types correctly', () => {
+      const items1 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.9, index: 0 },
+          { type: SearchScoreTypeEnum.reRank, value: 0.8, index: 0 }
+        ])
+      ];
+
+      const items2 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.7, index: 0 }
+        ])
+      ];
+
+      const input = [
+        { weight: 1.0, list: items1 },
+        { weight: 1.0, list: items2 }
+      ];
+
+      const result = datasetSearchResultConcat(input);
+
+      expect(result).toHaveLength(1);
+      expect(result[0].score).toHaveLength(4); // embedding, reRank, fullText, rrf
+
+      // Verify all score types exist
+      const scoreTypes = result[0].score.map((s) => s.type);
+      expect(scoreTypes).toContain(SearchScoreTypeEnum.embedding);
+      expect(scoreTypes).toContain(SearchScoreTypeEnum.fullText);
+      expect(scoreTypes).toContain(SearchScoreTypeEnum.reRank);
+      expect(scoreTypes).toContain(SearchScoreTypeEnum.rrf);
+    });
+
+    it('should take max value for same score types', () => {
+      const items1 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.9, index: 0 }
+        ])
+      ];
+
+      const items2 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.7, index: 0 } // Lower score
+        ])
+      ];
+
+      const input = [
+        { weight: 1.0, list: items1 },
+        { weight: 1.0, list: items2 }
+      ];
+
+      const result = datasetSearchResultConcat(input);
+
+      expect(result).toHaveLength(1);
+
+      const embeddingScore = result[0].score.find((s) => s.type === SearchScoreTypeEnum.embedding);
+      expect(embeddingScore).toBeDefined();
+      expect(embeddingScore!.value).toBe(0.9); // Should take higher value
+    });
+  });
+
+  describe('Sorting tests', () => {
+    it('should sort by RRF score descending', () => {
+      const items1 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.9, index: 0 }
+        ]),
+        createSearchItem('2', 'Question 2', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.8, index: 1 }
+        ]),
+        createSearchItem('3', 'Question 3', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.7, index: 2 }
+        ])
+      ];
+
+      const items2 = [
+        createSearchItem('3', 'Question 3', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.9, index: 0 }
+        ]), // First position, higher RRF
+        createSearchItem('2', 'Question 2', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.8, index: 1 }
+        ]),
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.7, index: 2 }
+        ]) // Third position, lower RRF
+      ];
+
+      const input = [
+        { weight: 1.0, list: items1 },
+        { weight: 1.0, list: items2 }
+      ];
+
+      const result = datasetSearchResultConcat(input);
+
+      expect(result).toHaveLength(3);
+
+      // Verify descending RRF score order
+      for (let i = 0; i < result.length - 1; i++) {
+        const currentRrf = result[i].score.find((s) => s.type === SearchScoreTypeEnum.rrf)!.value;
+        const nextRrf = result[i + 1].score.find((s) => s.type === SearchScoreTypeEnum.rrf)!.value;
+        expect(currentRrf).toBeGreaterThanOrEqual(nextRrf);
+      }
+
+      // item1 and item3 have same RRF score, but item1 should be first due to stable sort order
+      expect(['1', '3']).toContain(result[0].id);
+    });
+  });
+
+  describe('RRF score update tests', () => {
+    it('should update existing RRF scores when multiple lists', () => {
+      const items1 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.9, index: 0 },
+          { type: SearchScoreTypeEnum.rrf, value: 0.5, index: 0 } // Existing RRF score
+        ])
+      ];
+
+      const items2 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.7, index: 0 }
+        ])
+      ];
+
+      const input = [
+        { weight: 1.0, list: items1 },
+        { weight: 1.0, list: items2 }
+      ];
+
+      const result = datasetSearchResultConcat(input);
+
+      expect(result).toHaveLength(1);
+
+      const rrfScores = result[0].score.filter((s) => s.type === SearchScoreTypeEnum.rrf);
+      expect(rrfScores).toHaveLength(1); // Should only have one RRF score
+
+      // RRF score should be updated to calculated value, not the original 0.5
+      expect(rrfScores[0].value).not.toBe(0.5);
+      expect(rrfScores[0].value).toBeCloseTo(1.0 / 61 + 1.0 / 61, 6);
+      expect(rrfScores[0].index).toBe(0); // Index after sorting
+    });
+
+    it('should add RRF score for items without one when multiple lists', () => {
+      const items1 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.9, index: 0 }
+          // No RRF score
+        ])
+      ];
+
+      const items2 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.7, index: 0 }
+        ])
+      ];
+
+      const input = [
+        { weight: 1.0, list: items1 },
+        { weight: 1.0, list: items2 }
+      ];
+
+      const result = datasetSearchResultConcat(input);
+
+      expect(result).toHaveLength(1);
+
+      const rrfScore = result[0].score.find((s) => s.type === SearchScoreTypeEnum.rrf);
+      expect(rrfScore).toBeDefined();
+      expect(rrfScore!.value).toBeCloseTo(1.0 / 61 + 1.0 / 61, 6);
+      expect(rrfScore!.index).toBe(0);
+    });
+
+    it('should not modify single list (direct return)', () => {
+      const items1 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.9, index: 0 }
+        ])
+      ];
+
+      const input = [{ weight: 1.0, list: items1 }];
+
+      const result = datasetSearchResultConcat(input);
+
+      expect(result).toHaveLength(1);
+      expect(result).toEqual(items1); // Should be exactly the same as input
+
+      // Should not have RRF score because single list is returned directly
+      const rrfScore = result[0].score.find((s) => s.type === SearchScoreTypeEnum.rrf);
+      expect(rrfScore).toBeUndefined();
+    });
+  });
+
+  describe('Complex scenario tests', () => {
+    it('should handle complex multi-source merging', () => {
+      const embeddingResults = [
+        createSearchItem('doc1', 'AI Introduction', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.95, index: 0 }
+        ]),
+        createSearchItem('doc2', 'Machine Learning Basics', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.9, index: 1 }
+        ]),
+        createSearchItem('doc3', 'Deep Learning Principles', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.85, index: 2 }
+        ])
+      ];
+
+      const fullTextResults = [
+        createSearchItem('doc2', 'Machine Learning Basics', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.88, index: 0 }
+        ]),
+        createSearchItem('doc4', 'Neural Network Applications', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.82, index: 1 }
+        ]),
+        createSearchItem('doc1', 'AI Introduction', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.78, index: 2 }
+        ])
+      ];
+
+      const reRankResults = [
+        createSearchItem('doc3', 'Deep Learning Principles', [
+          { type: SearchScoreTypeEnum.reRank, value: 0.92, index: 0 }
+        ]),
+        createSearchItem('doc1', 'AI Introduction', [
+          { type: SearchScoreTypeEnum.reRank, value: 0.89, index: 1 }
+        ])
+      ];
+
+      const input = [
+        { weight: 1.0, list: embeddingResults },
+        { weight: 0.8, list: fullTextResults },
+        { weight: 1.2, list: reRankResults }
+      ];
+
+      const result = datasetSearchResultConcat(input);
+
+      // Should have 4 unique documents
+      expect(result).toHaveLength(4);
+
+      // Verify all documents have RRF scores
+      result.forEach((item) => {
+        const rrfScore = item.score.find((s) => s.type === SearchScoreTypeEnum.rrf);
+        expect(rrfScore).toBeDefined();
+        expect(rrfScore!.value).toBeGreaterThan(0);
+      });
+
+      // Verify merged scores
+      const doc1 = result.find((item) => item.id === 'doc1')!;
+      const doc1ScoreTypes = doc1.score.map((s) => s.type);
+      expect(doc1ScoreTypes).toContain(SearchScoreTypeEnum.embedding);
+      expect(doc1ScoreTypes).toContain(SearchScoreTypeEnum.fullText);
+      expect(doc1ScoreTypes).toContain(SearchScoreTypeEnum.reRank);
+      expect(doc1ScoreTypes).toContain(SearchScoreTypeEnum.rrf);
+
+      // Verify sorting by RRF score descending
+      for (let i = 0; i < result.length - 1; i++) {
+        const currentRrf = result[i].score.find((s) => s.type === SearchScoreTypeEnum.rrf)!.value;
+        const nextRrf = result[i + 1].score.find((s) => s.type === SearchScoreTypeEnum.rrf)!.value;
+        expect(currentRrf).toBeGreaterThanOrEqual(nextRrf);
+      }
+    });
+  });
+
+  describe('Edge weight tests', () => {
+    it('should handle zero weight', () => {
+      const items1 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.9, index: 0 }
+        ])
+      ];
+
+      const items2 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.7, index: 0 }
+        ])
+      ];
+
+      const input = [
+        { weight: 0, list: items1 },
+        { weight: 1.0, list: items2 }
+      ];
+
+      const result = datasetSearchResultConcat(input);
+
+      expect(result).toHaveLength(1);
+
+      const rrfScore = result[0].score.find((s) => s.type === SearchScoreTypeEnum.rrf);
+      expect(rrfScore).toBeDefined();
+      expect(rrfScore!.value).toBeCloseTo(1.0 / 61, 6); // Only from second list
+    });
+
+    it('should handle negative weight', () => {
+      const items1 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.9, index: 0 }
+        ])
+      ];
+
+      const items2 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.7, index: 0 }
+        ])
+      ];
+
+      const input = [
+        { weight: -1.0, list: items1 },
+        { weight: 1.0, list: items2 }
+      ];
+
+      const result = datasetSearchResultConcat(input);
+
+      expect(result).toHaveLength(1);
+
+      const rrfScore = result[0].score.find((s) => s.type === SearchScoreTypeEnum.rrf);
+      expect(rrfScore).toBeDefined();
+      // Should be: -1.0 * (1/61) + 1.0 * (1/61) = 0
+      expect(rrfScore!.value).toBeCloseTo(0, 6);
+    });
+
+    it('should handle very small weight', () => {
+      const items1 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.embedding, value: 0.9, index: 0 }
+        ])
+      ];
+
+      const items2 = [
+        createSearchItem('1', 'Question 1', [
+          { type: SearchScoreTypeEnum.fullText, value: 0.7, index: 0 }
+        ])
+      ];
+
+      const input = [
+        { weight: 0.001, list: items1 },
+        { weight: 1.0, list: items2 }
+      ];
+
+      const result = datasetSearchResultConcat(input);
+
+      expect(result).toHaveLength(1);
+
+      const rrfScore = result[0].score.find((s) => s.type === SearchScoreTypeEnum.rrf);
+      expect(rrfScore).toBeDefined();
+      expect(rrfScore!.value).toBeCloseTo(0.001 / 61 + 1.0 / 61, 6);
+    });
+  });
+});