better documentation

Author: cevian

README.md

@@ -178,7 +178,9 @@ You can create a timescale-vector index on the table with.
 await vec.create_embedding_index(client.TimescaleVectorIndex())
 ```
 
-You can drop the index with:
+Please see
+[`TimescaleVectorIndex`](https://timescale.github.io/python-vector/vector.html#timescalevectorindex)
+documentation for advanced options. the You can drop the index with:
 
 ``` python
 await vec.drop_embedding_index()
@@ -187,8 +189,10 @@ await vec.drop_embedding_index()
 While we recommend the timescale-vector index type, we also have 2 more
 index types availabe:
 
-- The pgvector ivfflat index
-- The pgvector hnsw index
+- The pgvector ivfflat index with
+  [`IvfflatIndex`](https://timescale.github.io/python-vector/vector.html#ivfflatindex)
+- The pgvector hnsw index with
+  [`HNSWIndex`](https://timescale.github.io/python-vector/vector.html#hnswindex)
 
 Usage examples below:
 

nbs/00_vector.ipynb

@@ -165,6 +165,9 @@
     "\n",
     "class IvfflatIndex(BaseIndex):\n",
     "    def __init__(self, num_records: Optional[int] = None, num_lists: Optional[int] = None) -> None:\n",
+    "        \"\"\"\n",
+    "        Pgvector's ivfflat index.\n",
+    "        \"\"\"\n",
     "        self.num_records = num_records\n",
     "        self.num_lists = num_lists\n",
     "    \n",
@@ -196,6 +199,9 @@
     "\n",
     "class HNSWIndex(BaseIndex):\n",
     "    def __init__(self, m: Optional[int] = None, ef_construction: Optional[int] = None) -> None:\n",
+    "        \"\"\"\n",
+    "        Pgvector's hnsw index.\n",
+    "        \"\"\"\n",
     "        self.m = m\n",
     "        self.ef_construction = ef_construction\n",
     "\n",
@@ -223,6 +229,9 @@
     "                 max_alpha: Optional[float] = None,\n",
     "                 pq_vector_length: Optional[int] = None,\n",
     "                 ) -> None:\n",
+    "        \"\"\"\n",
+    "        Timescale's vector index.\n",
+    "        \"\"\"\n",
     "        self.use_pq = use_pq\n",
     "        self.num_neighbors = num_neighbors\n",
     "        self.search_list_size = search_list_size\n",

nbs/index.ipynb

@@ -514,7 +514,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "You can drop the index with:"
+    "Please see `TimescaleVectorIndex` documentation for advanced options. the You can drop the index with:"
    ]
   },
   {
@@ -533,8 +533,8 @@
    "source": [
     "While we recommend the timescale-vector index type, we also have 2 more index types availabe:\n",
     "\n",
-    "* The pgvector ivfflat index\n",
-    "* The pgvector hnsw index\n",
+    "* The pgvector ivfflat index with `IvfflatIndex`\n",
+    "* The pgvector hnsw index with `HNSWIndex`\n",
     "\n",
     "Usage examples below:"
    ]

timescale_vector/client.py

@@ -91,6 +91,9 @@ def create_index_query(self, table_name_quoted:str, column_name_quoted: str, ind
 
 class IvfflatIndex(BaseIndex):
     def __init__(self, num_records: Optional[int] = None, num_lists: Optional[int] = None) -> None:
+        """
+        Pgvector's ivfflat index.
+        """
         self.num_records = num_records
         self.num_lists = num_lists
 
@@ -122,6 +125,9 @@ def create_index_query(self, table_name_quoted:str, column_name_quoted: str, ind
 
 class HNSWIndex(BaseIndex):
     def __init__(self, m: Optional[int] = None, ef_construction: Optional[int] = None) -> None:
+        """
+        Pgvector's hnsw index.
+        """
         self.m = m
         self.ef_construction = ef_construction
 
@@ -149,6 +155,9 @@ def __init__(self,
                  max_alpha: Optional[float] = None,
                  pq_vector_length: Optional[int] = None,
                  ) -> None:
+        """
+        Timescale's vector index.
+        """
         self.use_pq = use_pq
         self.num_neighbors = num_neighbors
         self.search_list_size = search_list_size