Release new docs

v2.3.x/site/en/userGuide/search/hybridsearch.md

@@ -1,13 +1,13 @@
 ---
 id: hybridsearch.md
-label: Conduct a Hybrid Search
+label: Hybrid Search
 related_key: filter
 order: 1
 group: search.md
 summary: Conduct a Hybrid Search with Milvus.
 ---
 
-<div class="tab-wrapper"><a href="search.md" class=''>Conduct a Vector Similarity Search</a><a href="hybridsearch.md" class='active '>Conduct a Hybrid Search</a><a href="within_range.md" class=''>Conduct a Range Search</a></div>
+<div class="tab-wrapper"><a href="search.md" class=''>Vector Similarity Search</a><a href="hybridsearch.md" class='active '>Hybrid Search</a><a href="within_range.md" class=''>Range Search</a></div>
 
 # Conduct a Hybrid Search
 

v2.3.x/site/en/userGuide/search/search.md

@@ -1,13 +1,13 @@
 ---
 id: search.md
-label: Conduct a Vector Similarity Search
+label: Vector Similarity Search
 related_key: search
 order: 0
 group: search.md
 summary: Conduct a vector similarity search with Milvus.
 ---
 
-<div class="tab-wrapper"><a href="search.md" class='active '>Conduct a Vector Similarity Search</a><a href="hybridsearch.md" class=''>Conduct a Hybrid Search</a><a href="within_range.md" class=''>Conduct a Range Search</a></div>
+<div class="tab-wrapper"><a href="search.md" class='active '>Vector Similarity Search</a><a href="hybridsearch.md" class=''>Hybrid Search</a><a href="within_range.md" class=''>Range Search</a></div>
 
 # Conduct a Vector Similarity Search
 
@@ -212,8 +212,11 @@ Output:
     </tr>    
     <tr>
         <td><code>params</code></td>
-        <td>Search parameter(s) specific to the specified index type. See <a href="index.md">Vector Index</a> for more information. Possible options are as follows: <ul><li><code>nprobe</code> Indicates the number of cluster units to search. This parameter is available only when <code>index_type</code> is set to <code>IVF_FLAT</code>, <code>IVF_SQ8</code>, or <code>IVF_PQ</code>. The value should be less than <code>nlist</code> specified for the index-building process.</li>
-            <li><code>ef</code> Indicates the search scope. This parameter is available only when <code>index_type</code> is set to <code>HNSW</code>. The value should be within the range from <code>top_k</code> to <code>32768</code>.</li>
+        <td>Search parameter(s) specific to the specified index type. See <a href="index.md">Vector Index</a> for more information. Possible options are as follows: <ul>
+        <li><code>nprobe</code> Indicates the number of cluster units to search. This parameter is available only when <code>index_type</code> is set to <code>IVF_FLAT</code>, <code>IVF_SQ8</code>, or <code>IVF_PQ</code>. The value should be less than <code>nlist</code> specified for the index-building process.</li>
+        <li><code>ef</code> Indicates the search scope. This parameter is available only when <code>index_type</code> is set to <code>HNSW</code>. The value should be within the range from <code>top_k</code> to <code>32768</code>.</li>
+        <li><code>radius</code> Indicates the angle where the vector with the least similarity resides.</li>
+        <li><code>range_filter</code> Indicates the filter used to filter vector field values whose similarity to the query vector falls into a specific range.</li>
         </ul></td>
     </tr>
     </tbody>

v2.3.x/site/en/userGuide/search/with_iterators.md

@@ -9,7 +9,7 @@ summary: Learn how to search and query data with iterators.
 
 <div class="tab-wrapper"><a href="query.md" class=''>Conduct a Query</a><a href="with_iterators.md" class='active '>Conduct a Query with Iterators</a></div>
 
-# With Iterators
+# Conduct a Query With Iterators
 
 This topic describes how to search and query data with iterators.
 

v2.3.x/site/en/userGuide/search/within_range.md

@@ -1,15 +1,15 @@
 ---
 id: within_range.md
-label: Conduct a Range Search
+label: Range Search
 related_key: Within Range
 order: 2
 group: search.md
 summary: Learn how to conduct a range search.
 ---
 
-<div class="tab-wrapper"><a href="search.md" class=''>Conduct a Vector Similarity Search</a><a href="hybridsearch.md" class=''>Conduct a Hybrid Search</a><a href="within_range.md" class='active '>Conduct a Range Search</a></div>
+<div class="tab-wrapper"><a href="search.md" class=''>Vector Similarity Search</a><a href="hybridsearch.md" class=''>Hybrid Search</a><a href="within_range.md" class='active '>Range Search</a></div>
 
-# Within Range
+# Conduct a Vector Similarity Search Within a Range
 
 This topic describes how to conduct a range search.
 
@@ -134,9 +134,9 @@ In terms of L2 distance, conduct a range search that returns vectors with a simi
 search_param = {
   "data": [[0.1, 0.2]], # query vector
   "anns_field": "book_intro", # name of the field to search on
-  "param": {"metric_type": "L2", "nprobe": 10, "radius": 10.0, "range_filter" : 5.0, "offset": 0},
+  "param": { "metric_type": "L2", "params": { "nprobe": 10, "radius": 10.0, "range_filter" : 5.0 }, "offset": 0 },
   "limit": 2,
-  output_fields=["int64", "float"] # fields to return
+  "output_fields": ["int64", "float"]  # fields to return
 }
 
 res = collection.search(**search_param)
@@ -171,9 +171,9 @@ In terms of IP distance, conduct a range search that returns vectors with a simi
 search_param = {
   "data": [[0.1, 0.2]], # query vector
   "anns_field": "book_intro", # name of the field to search on
-  "param": {"metric_type": "IP", "nprobe": 10, "radius": 0.8, "range_filter" : 1.0, "offset": 0},
+  "param": {"metric_type": "IP", "params": { "nprobe": 10, "radius": 0.8, "range_filter" : 1.0 }, "offset": 0 },
   "limit": 2,
-  output_fields=["int64", "float"] # fields to return
+  "output_fields": ["int64", "float"] # fields to return
 }
 
 res = collection.search(**search_param)