PR #551 (#14)

(cherry picked from commit b80329d)

site/en/guides/milvus_operation.md

@@ -140,7 +140,7 @@ Currently, a collection only supports one index type, and switching the index ty
    ```python
    >>> import random
    # Generate 20 vectors of 256 dimension
-   >>> vectors = [[random.random() for _ in range(dim)] for _ in range(20)]
+   >>> vectors = [[random.random() for _ in range(256)] for _ in range(20)]
    ```
 
 2. Insert the list of vectors. If you do not specify vector ids, Milvus automatically generates IDs for the vectors.
@@ -224,17 +224,17 @@ A segment is a data file that Milvus automatically creates by merging inserted v
 2. Search vectors.
 
    ```python
-   # create 5 vectors of 32-dimension
-   >>> q_records = [[random.random() for _ in range(dim)] for _ in range(5)]
+   # create 5 vectors of 256-dimension
+   >>> q_records = [[random.random() for _ in range(256)] for _ in range(5)]
    # search vectors
    >>> milvus.search(collection_name='test01', query_records=q_records, top_k=2, params=search_param)
    ```
 
 #### Search vectors in a partition
 
 ```python
-# create 5 vectors of 32-dimension
->>> q_records = [[random.random() for _ in range(dim)] for _ in range(5)]
+# create 5 vectors of 256-dimension
+>>> q_records = [[random.random() for _ in range(256)] for _ in range(5)]
 >>> milvus.search(collection_name='test01', query_records=q_records, top_k=1, partition_tags=['tag01'], params=search_param)
 ```
 

site/en/menuStructure/en.json

@@ -1,7 +1,7 @@
 {
   "menuList": [
   {
-      "id": "about_milvus",
+      "id": "aboutmilvus",
       "title": "About Milvus",
       "lang": "en",
       "label1": "",
@@ -14,7 +14,7 @@
       "id": "overview.md",
       "title": "Milvus Overview",
       "lang": "en",
-      "label1": "about_milvus",
+      "label1": "aboutmilvus",
       "label2": null,
       "label3": null,
       "order": 0
@@ -23,7 +23,7 @@
       "id": "vector.md",
       "title": "Feature Vector",
       "lang": "en",
-      "label1": "about_milvus",
+      "label1": "aboutmilvus",
       "label2": null,
       "label3": null,
       "order": 1
@@ -32,7 +32,7 @@
       "id": "traditional_db.md",
       "title": "Traditional Databases",
       "lang": "en",
-      "label1": "about_milvus",
+      "label1": "aboutmilvus",
       "label2": null,
       "label3": null,
       "order": 2
@@ -41,7 +41,7 @@
       "id": "index_method.md",
       "title": "Vector Search Methods",
       "lang": "en",
-      "label1": "about_milvus",
+      "label1": "aboutmilvus",
       "label2": null,
       "label3": null,
       "order": 3
@@ -50,7 +50,7 @@
       "id": "vector_db.md",
       "title": "Other Feature Vector Search Tools",
       "lang": "en",
-      "label1": "about_milvus",
+      "label1": "aboutmilvus",
       "label2": null,
       "label3": null,
       "order": 4

site/zh-CN/guides/milvus_operation.md

@@ -133,7 +133,7 @@ sidebar_label: Learn Milvus Operations
    ```python
    >>> import random
    # Generate 20 vectors of 256 dimension
-   >>> vectors = [[random.random() for _ in range(dim)] for _ in range(20)]
+   >>> vectors = [[random.random() for _ in range(256)] for _ in range(20)]
    ```
 
 2. 插入向量列表。如果你不指定向量 ID，Milvus 自动为向量分配 ID。
@@ -227,16 +227,16 @@ Segment 是 Milvus 自动将插入的向量数据合并所获得的数据文件
 2. 创建随机向量作为 `query_records` 进行搜索。
 
    ```python
-   # create 5 vectors of 32-dimension
-   >>> q_records = [[random.random() for _ in range(dim)] for _ in range(5)]
+   # create 5 vectors of 256-dimension
+   >>> q_records = [[random.random() for _ in range(256)] for _ in range(5)]
    >>> milvus.search(collection_name='test01', query_records=q_records, top_k=2, params=search_param)
    ```
 
 #### 在分区中搜索向量
 
 ```python
-# create 5 vectors of 32-dimension
->>> q_records = [[random.random() for _ in range(dim)] for _ in range(5)]
+# create 5 vectors of 256-dimension
+>>> q_records = [[random.random() for _ in range(256)] for _ in range(5)]
 >>> milvus.search(collection_name='test01', query_records=q_records, top_k=1, partition_tags=['tag01'], params=search_param)
 ```