Give a name to the distance result column in the query

Author: cevian

README.md

@@ -74,24 +74,24 @@ Now you can query for similar items:
 await vec.search([1.0, 9.0])
 ```
 
-    [<Record id=UUID('ae68bcbf-52e7-4977-b4b9-d2c954c3b8b4') metadata='{"action": "jump", "animal": "fox"}' contents='jumped over the' embedding=array([ 1. , 10.8], dtype=float32) ?column?=0.00016793422934946456>,
-     <Record id=UUID('a76f2c30-f001-4e1a-abed-a2a0ce6aa8fe') metadata='{"animal": "fox"}' contents='the brown fox' embedding=array([1. , 1.3], dtype=float32) ?column?=0.14489260377438218>]
+    [<Record id=UUID('393ef5c7-1587-468e-870c-b9a6a6716321') metadata='{"action": "jump", "animal": "fox"}' contents='jumped over the' embedding=array([ 1. , 10.8], dtype=float32) distance=0.00016793422934946456>,
+     <Record id=UUID('7bec0df8-463f-4ea9-8d50-197906f9237e') metadata='{"animal": "fox"}' contents='the brown fox' embedding=array([1. , 1.3], dtype=float32) distance=0.14489260377438218>]
 
 You can specify the number of records to return.
 
 ``` python
 await vec.search([1.0, 9.0], k=1)
 ```
 
-    [<Record id=UUID('ae68bcbf-52e7-4977-b4b9-d2c954c3b8b4') metadata='{"action": "jump", "animal": "fox"}' contents='jumped over the' embedding=array([ 1. , 10.8], dtype=float32) ?column?=0.00016793422934946456>]
+    [<Record id=UUID('393ef5c7-1587-468e-870c-b9a6a6716321') metadata='{"action": "jump", "animal": "fox"}' contents='jumped over the' embedding=array([ 1. , 10.8], dtype=float32) distance=0.00016793422934946456>]
 
 You can also specify a filter on the metadata as a simple dictionary
 
 ``` python
 await vec.search([1.0, 9.0], k=1, filter={"action": "jump"})
 ```
 
-    [<Record id=UUID('ae68bcbf-52e7-4977-b4b9-d2c954c3b8b4') metadata='{"action": "jump", "animal": "fox"}' contents='jumped over the' embedding=array([ 1. , 10.8], dtype=float32) ?column?=0.00016793422934946456>]
+    [<Record id=UUID('393ef5c7-1587-468e-870c-b9a6a6716321') metadata='{"action": "jump", "animal": "fox"}' contents='jumped over the' embedding=array([ 1. , 10.8], dtype=float32) distance=0.00016793422934946456>]
 
 ## Advanced Usage
 

nbs/00_vector.ipynb

@@ -222,7 +222,7 @@
     "            params = params + [json_object]\n",
     "        query = '''\n",
     "        SELECT\n",
-    "            id, metadata, contents, embedding, {distance}\n",
+    "            id, metadata, contents, embedding, {distance} as distance\n",
     "        FROM\n",
     "           {table_name}\n",
     "        WHERE \n",

nbs/index.ipynb

@@ -188,8 +188,8 @@
     {
      "data": {
       "text/plain": [
-       "[<Record id=UUID('ae68bcbf-52e7-4977-b4b9-d2c954c3b8b4') metadata='{\"action\": \"jump\", \"animal\": \"fox\"}' contents='jumped over the' embedding=array([ 1. , 10.8], dtype=float32) ?column?=0.00016793422934946456>,\n",
-       " <Record id=UUID('a76f2c30-f001-4e1a-abed-a2a0ce6aa8fe') metadata='{\"animal\": \"fox\"}' contents='the brown fox' embedding=array([1. , 1.3], dtype=float32) ?column?=0.14489260377438218>]"
+       "[<Record id=UUID('393ef5c7-1587-468e-870c-b9a6a6716321') metadata='{\"action\": \"jump\", \"animal\": \"fox\"}' contents='jumped over the' embedding=array([ 1. , 10.8], dtype=float32) distance=0.00016793422934946456>,\n",
+       " <Record id=UUID('7bec0df8-463f-4ea9-8d50-197906f9237e') metadata='{\"animal\": \"fox\"}' contents='the brown fox' embedding=array([1. , 1.3], dtype=float32) distance=0.14489260377438218>]"
       ]
      },
      "execution_count": null,
@@ -216,7 +216,7 @@
     {
      "data": {
       "text/plain": [
-       "[<Record id=UUID('ae68bcbf-52e7-4977-b4b9-d2c954c3b8b4') metadata='{\"action\": \"jump\", \"animal\": \"fox\"}' contents='jumped over the' embedding=array([ 1. , 10.8], dtype=float32) ?column?=0.00016793422934946456>]"
+       "[<Record id=UUID('393ef5c7-1587-468e-870c-b9a6a6716321') metadata='{\"action\": \"jump\", \"animal\": \"fox\"}' contents='jumped over the' embedding=array([ 1. , 10.8], dtype=float32) distance=0.00016793422934946456>]"
       ]
      },
      "execution_count": null,
@@ -243,7 +243,7 @@
     {
      "data": {
       "text/plain": [
-       "[<Record id=UUID('ae68bcbf-52e7-4977-b4b9-d2c954c3b8b4') metadata='{\"action\": \"jump\", \"animal\": \"fox\"}' contents='jumped over the' embedding=array([ 1. , 10.8], dtype=float32) ?column?=0.00016793422934946456>]"
+       "[<Record id=UUID('393ef5c7-1587-468e-870c-b9a6a6716321') metadata='{\"action\": \"jump\", \"animal\": \"fox\"}' contents='jumped over the' embedding=array([ 1. , 10.8], dtype=float32) distance=0.00016793422934946456>]"
       ]
      },
      "execution_count": null,

timescale_vector/client.py

@@ -156,7 +156,7 @@ def search_query(self, query_embedding: List[float], k: int=10, filter: Optional
             params = params + [json_object]
         query = '''
         SELECT
-            id, metadata, contents, embedding, {distance}
+            id, metadata, contents, embedding, {distance} as distance
         FROM
            {table_name}
         WHERE