Polish

docs/docs_skeleton/docs/modules/data_connection/document_transformers/text_splitters/code_splitter.mdx

@@ -1,6 +1,6 @@
-# Split code
+# Split code and markup
 
-CodeTextSplitter allows you to split your code with multiple language support.
+CodeTextSplitter allows you to split your code and markup with support for multiple languages.
 
 import Example from "@snippets/modules/data_connection/document_transformers/text_splitters/code_splitter.mdx"
 

docs/snippets/modules/model_io/models/llms/how_to/llm_caching.mdx

@@ -1,3 +1,5 @@
+import CodeBlock from "@theme/CodeBlock";
+
 ```typescript
 import { OpenAI } from "langchain/llms/openai";
 
@@ -42,3 +44,61 @@ console.log(res2);
   "\n\nWhy did the chicken cross the road?\n\nTo get to the other side."
 */
 ```
+
+## Caching with Momento
+
+LangChain also provides a Momento-based cache. [Momento](https://gomomento.com) is a distributed, serverless cache that requires zero setup or infrastructure maintenance. To use it, you'll need to install the `@gomomento/sdk` package:
+
+```bash npm2yarn
+npm install @gomomento/sdk
+```
+
+Next you'll need to sign up and create an API key. Once you've done that, pass a `cache` option when you instantiate the LLM like this:
+
+import MomentoCacheExample from "@examples/cache/momento.ts";
+
+<CodeBlock language="typescript">{MomentoCacheExample}</CodeBlock>
+
+## Caching with Redis
+
+LangChain also provides a Redis-based cache. This is useful if you want to share the cache across multiple processes or servers. To use it, you'll need to install the `redis` package:
+
+```bash npm2yarn
+npm install redis
+```
+
+Then, you can pass a `cache` option when you instantiate the LLM. For example:
+
+```typescript
+import { OpenAI } from "langchain/llms/openai";
+import { RedisCache } from "langchain/cache/redis";
+import { createClient } from "redis";
+
+// See https://github.com/redis/node-redis for connection options
+const client = createClient();
+const cache = new RedisCache(client);
+
+const model = new OpenAI({ cache });
+```
+
+## Caching with Upstash Redis
+
+LangChain also provides an Upstash Redis-based cache. Like the Redis-based cache, this cache is useful if you want to share the cache across multiple processes or servers. The Upstash Redis client uses HTTP and supports edge environments. To use it, you'll need to install the `@upstash/redis` package:
+
+```bash npm2yarn
+npm install @upstash/redis
+```
+
+You'll also need an [Upstash account](https://docs.upstash.com/redis#create-account) and a [Redis database](https://docs.upstash.com/redis#create-a-database) to connect to. Once you've done that, retrieve your REST URL and REST token.
+
+Then, you can pass a `cache` option when you instantiate the LLM. For example:
+
+import UpstashRedisCacheExample from "@examples/cache/upstash_redis.ts";
+
+<CodeBlock language="typescript">{UpstashRedisCacheExample}</CodeBlock>
+
+You can also directly pass in a previously created [@upstash/redis](https://docs.upstash.com/redis/sdks/javascriptsdk/overview) client instance:
+
+import AdvancedUpstashRedisCacheExample from "@examples/cache/upstash_redis_advanced.ts";
+
+<CodeBlock language="typescript">{AdvancedUpstashRedisCacheExample}</CodeBlock>