Add concurrency in GenAI example

Author: stefano-ottolenghi

modules/ROOT/pages/genai-integrations.adoc

@@ -180,24 +180,26 @@ MATCH (m:Movie WHERE m.plot IS NOT NULL)
 WITH collect(m) AS moviesList, // <1>
      count(*) AS total,
      100 AS batchSize // <2>
-UNWIND range(0, total, batchSize) AS batchStart // <3>
+UNWIND range(0, total-1, batchSize) AS batchStart // <3>
 CALL (moviesList, batchStart, batchSize) { // <4>
     WITH [movie IN moviesList[batchStart .. batchStart + batchSize] | movie.title || ': ' || movie.plot] AS batch // <5>
     CALL genai.vector.encodeBatch(batch, 'OpenAI', { token: $token }) YIELD index, vector
     CALL db.create.setNodeVectorProperty(moviesList[batchStart + index], 'embedding', vector) // <6>
-} IN TRANSACTIONS OF 1 ROW <7>
+} IN CONCURRENT TRANSACTIONS OF 1 ROW <7>
 ----
 
 <1> xref:functions/aggregating.adoc#functions-collect[Collect] all returned `Movie` nodes into a `LIST<NODE>`.
 <2> `batchSize` defines the number of nodes in `moviesList` to be processed at once.
 Because vector embeddings can be very large, a larger batch size may require significantly more memory on the Neo4j server.
 Too large a batch size may also exceed the provider's threshold.
 <3> Process `Movie` nodes in increments of `batchSize`.
+The end range `total-1` is due to `range` being inclusive on both ends.
 <4> A xref:subqueries/subqueries-in-transactions.adoc[`CALL` subquery] executes a separate transaction for each batch.
 Note that this `CALL` subquery uses a xref:subqueries/call-subquery.adoc#variable-scope-clause[variable scope clause].
 <5> `batch` is a list of strings, each being the concatenation of `title` and `plot` of one movie.
 <6> The procedure sets `vector` as value for the property named `embedding` for the node at position `batchStart + index` in the `moviesList`.
 <7> Set to `1` the amount of batches to be processed at once.
+For more information on concurrency in transactions, see xref:subqueries/subqueries-in-transactions.adoc#concurrent-transactions[`CALL` subqueries -> Concurrent transactions]).
 
 [NOTE]
 This example may not scale to larger datasets, as `collect(m)` requires the whole result set to be loaded in memory.