Swap to client examples for all examples

Author: cmilesb

content/develop/ai/langcache/api-examples.md

@@ -35,7 +35,7 @@ curl -s -X POST "https://$HOST/v1/caches/$CACHE_ID/entries/search" \
     -d "{ 'prompt': 'What is semantic caching' }"
 {{< /clients-example >}}
 
-- The example expects several variables to be set in the shell:
+This example expects several variables to be set in the shell:
 
     - **$HOST** - the LangCache API base URL
     - **$CACHE_ID** - the Cache ID of your cache
@@ -74,75 +74,19 @@ POST https://[host]/v1/caches/{cacheId}/entries/search
 
 Use [`POST /v1/caches/{cacheId}/entries`]({{< relref "/develop/ai/langcache/api-reference#tag/Cache-Entries/operation/set" >}}) to store a new response in the cache.
 
-{{< multitabs id="store-basic"
-    tab1="REST API"
-    tab2="Python"
-    tab3="Javascript" >}}
-
-```sh
+{{< clients-example set="langcache_sdk" step="store_basic" dft_tab_name="REST API" footer="hide" >}}
 POST https://[host]/v1/caches/{cacheId}/entries
 {
     "prompt": "User prompt text",
     "response": "LLM response text"
 }
-```
-
--tab-sep-
-
-```python
-from langcache import LangCache
-import os
-
-
-with LangCache(
-    server_url="https://[host]",
-    cache_id="{cacheId}",
-    service_key=os.getenv("LANGCACHE_SERVICE_KEY", ""),
-) as lang_cache:
-
-    res = lang_cache.set(
-        prompt="User prompt text",
-        response="LLM response text",
-    )
-
-    print(res)
-```
-
--tab-sep-
-
-```js
-import { LangCache } from "@redis-ai/langcache";
-
-const langCache = new LangCache({
-  serverURL: "https://<host>",
-  cacheId: "<cacheId>",
-  serviceKey: "<LANGCACHE_SERVICE_KEY>",
-});
-
-async function run() {
-  const result = await langCache.set({
-    prompt: "User prompt text",
-    response: "LLM response text",
-  });
-
-  console.log(result);
-}
-
-run();
-```
-
-{{< /multitabs >}}
+{{< /clients-example >}}
 
 Place this call in your client app after you get a response from the LLM. This will store the response in the cache for future use.
 
 You can also store the responses with custom attributes by adding an `attributes` object to the request.
 
-{{< multitabs id="store-attributes"
-    tab1="REST API"
-    tab2="Python"
-    tab3="Javascript" >}}
-
-```sh
+{{< clients-example set="langcache_sdk" step="store_attributes" dft_tab_name="REST API" footer="hide" >}}
 POST https://[host]/v1/caches/{cacheId}/entries
 {
     "prompt": "User prompt text",
@@ -151,110 +95,15 @@ POST https://[host]/v1/caches/{cacheId}/entries
         "customAttributeName": "customAttributeValue"
     }
 }
-```
--tab-sep-
-
-```python
-from langcache import LangCache
-import os
-
-
-with LangCache(
-    server_url="https://[host]",
-    cache_id="{cacheId}",
-    service_key=os.getenv("LANGCACHE_SERVICE_KEY", ""),
-) as lang_cache:
-
-    res = lang_cache.set(
-        prompt="User prompt text",
-        response="LLM response text",
-        attributes={"customAttributeName": "customAttributeValue"},
-    )
-
-    print(res)
-```
-
--tab-sep-
-
-```js
-import { LangCache } from "@redis-ai/langcache";
-
-const langCache = new LangCache({
-  serverURL: "https://<host>",
-  cacheId: "<cacheId>",
-  serviceKey: "<LANGCACHE_SERVICE_KEY>",
-});
-
-async function run() {
-  const result = await langCache.set({
-    prompt: "User prompt text",
-    response: "LLM response text",
-    attributes: {
-      "customAttributeName": "customAttributeValue",
-    },
-  });
-
-  console.log(result);
-}
-
-run();
-```
-
-{{< /multitabs >}}
+{{< /clients-example >}}
 
 ### Delete cached responses
 
 Use [`DELETE /v1/caches/{cacheId}/entries/{entryId}`]({{< relref "/develop/ai/langcache/api-reference#tag/Cache-Entries/operation/delete" >}}) to delete a cached response from the cache.
 
-{{< multitabs id="delete-entry"
-    tab1="REST API"
-    tab2="Python"
-    tab3="Javascript" >}}
-
-```sh
+{{< clients-example set="langcache_sdk" step="delete_entry" dft_tab_name="REST API" footer="hide" >}}
 DELETE https://[host]/v1/caches/{cacheId}/entries/{entryId}
-```
--tab-sep-
-
-```python
-from langcache import LangCache
-import os
-
-
-with LangCache(
-    server_url="https://[host]",
-    cache_id="{cacheId}",
-    service_key=os.getenv("LANGCACHE_SERVICE_KEY", ""),
-) as lang_cache:
-
-    res = lang_cache.delete_by_id(entry_id="{entryId}")
-
-    print(res)
-```
-
--tab-sep-
-
-```js
-import { LangCache } from "@redis-ai/langcache";
-
-const langCache = new LangCache({
-  serverURL: "https://<host>",
-  cacheId: "<cacheId>",
-  serviceKey: "<LANGCACHE_SERVICE_KEY>",
-});
-
-async function run() {
-  const result = await langCache.deleteById({
-    entryId: "<entryId>",
-  });
-
-  console.log(result);
-}
-
-run();
-```
-
-{{< /multitabs >}}
+{{< /clients-example >}}
 
 You can also use [`DELETE /v1/caches/{cacheId}/entries`]({{< relref "/develop/ai/langcache/api-reference#tag/Cache-Entries/operation/deleteQuery" >}}) to delete multiple cached responses based on the `attributes` you specify. If you specify multiple `attributes`, LangCache will delete entries that contain all given attributes. 
 
@@ -264,63 +113,12 @@ If you do not specify any `attributes`, all responses in the cache will be delet
 
 <br/>
 
-{{< multitabs id="delete-attributes"
-    tab1="REST API"
-    tab2="Python"
-    tab3="Javascript" >}}
-
-```sh
+{{< clients-example set="langcache_sdk" step="delete_query" dft_tab_name="REST API" footer="hide" >}}
 DELETE https://[host]/v1/caches/{cacheId}/entries
 {
     "attributes": {
         "customAttributeName": "customAttributeValue"
     }
 }
-```
-
--tab-sep-
-
-```python
-from langcache import LangCache
-import os
-
-
-with LangCache(
-    server_url="https://[host]",
-    cache_id="{cacheId}",
-    service_key=os.getenv("LANGCACHE_SERVICE_KEY", ""),
-) as lang_cache:
-
-    res = lang_cache.delete_query(
-        attributes={"customAttributeName": "customAttributeValue"},
-    )
-
-    print(res)
-```
-
--tab-sep-
-
-```js
-import { LangCache } from "@redis-ai/langcache";
-
-const langCache = new LangCache({
-  serverURL: "https://<host>",
-  cacheId: "<cacheId>",
-  serviceKey: "<LANGCACHE_SERVICE_KEY>",
-});
-
-async function run() {
-  const result = await langCache.deleteQuery({
-    attributes: {
-      "customAttributeName": "customAttributeValue",
-    },
-  });
-
-  console.log(result);
-}
-
-run();
-```
-
-{{< /multitabs >}}
+{{< /clients-example >}}