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Merge pull request #1841 from redis/DOC-5475
LangCache: Add API YAML for API reference
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‎content/develop/ai/langcache/api-examples.md‎

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---
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alwaysopen: false
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categories:
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- docs
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- develop
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- ai
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description: Learn to use the Redis LangCache API for semantic caching.
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hideListLinks: true
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linktitle: API and SDK examples
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title: Use the LangCache API and SDK
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weight: 10
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---
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Use the LangCache API from your client app to store and retrieve LLM, RAG, or agent responses.
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To access the LangCache API, you need:
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- LangCache API base URL
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- LangCache service API key
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- Cache ID
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When you call the API, you need to pass the LangCache API key in the `Authorization` header as a Bearer token and the Cache ID as the `cacheId` path parameter.
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For example, to search the cache using `cURL`:
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```bash
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curl -s -X POST "https://$HOST/v1/caches/$CACHE_ID/entires/search" \
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-H "accept: application/json" \
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-H "Authorization: Bearer $API_KEY" \
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-d "{ 'prompt': 'What is semantic caching' }"
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```
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- The example expects several variables to be set in the shell:
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- **$HOST** - the LangCache API base URL
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- **$CACHE_ID** - the Cache ID of your cache
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- **$API_KEY** - The LangCache API token
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{{% info %}}
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This example uses `cURL` and Linux shell scripts to demonstrate the API; you can use any standard REST client or library.
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{{% /info %}}
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You can also use the [LangCache SDKs](#langcache-sdk) for Javascript and Python to access the API.
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## API examples
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### Search LangCache for similar responses
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Use `POST /v1/caches/{cacheId}/entries/search` to search the cache for matching responses to a user prompt.
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```sh
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POST https://[host]/v1/caches/{cacheId}/entries/search
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{
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"prompt": "User prompt text"
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}
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```
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Place this call in your client app right before you call your LLM's REST API. If LangCache returns a response, you can send that response back to the user instead of calling the LLM.
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If LangCache does not return a response, you should call your LLM's REST API to generate a new response. After you get a response from the LLM, you can [store it in LangCache](#store-a-new-response-in-langcache) for future use.
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You can also scope the responses returned from LangCache by adding an `attributes` object to the request. LangCache will only return responses that match the attributes you specify.
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```sh
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POST https://[host]/v1/caches/{cacheId}/entries/search
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{
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"prompt": "User prompt text",
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"attributes": {
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"customAttributeName": "customAttributeValue"
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}
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}
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```
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### Store a new response in LangCache
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Use `POST /v1/caches/{cacheId}/entries` to store a new response in the cache.
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```sh
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POST https://[host]/v1/caches/{cacheId}/entries
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{
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"prompt": "User prompt text",
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"response": "LLM response text"
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}
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```
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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.
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You can also store the responses with custom attributes by adding an `attributes` object to the request.
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```sh
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POST https://[host]/v1/caches/{cacheId}/entries
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{
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"prompt": "User prompt text",
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"response": "LLM response text",
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"attributes": {
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"customAttributeName": "customAttributeValue"
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}
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}
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```
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### Delete cached responses
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Use `DELETE /v1/caches/{cacheId}/entries/{entryId}` to delete a cached response from the cache.
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You can also use `DELETE /v1/caches/{cacheId}/entries` to delete multiple cached responses at once. If you provide an `attributes` object, LangCache will delete all responses that match the attributes you specify.
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```sh
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DELETE https://[host]/v1/caches/{cacheId}/entries
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{
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"attributes": {
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"customAttributeName": "customAttributeValue"
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}
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}
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```
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## LangCache SDK
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If your app is written in Javascript or Python, you can also use the LangCache Software Development Kits (SDKs) to access the API.
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To learn how to use the LangCache SDKs:
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- [LangCache SDK for Javascript](https://www.npmjs.com/package/@redis-ai/langcache)
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- [LangCache SDK for Python](https://pypi.org/project/langcache/)

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

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---
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alwaysopen: false
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categories:
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- docs
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- develop
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- ai
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description: Learn to use the Redis LangCache API for semantic caching.
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hideListLinks: true
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linktitle: API and SDK reference
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title: LangCache API and SDK reference
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weight: 10
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---
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You can use the LangCache API from your client app to store and retrieve LLM, RAG, or agent responses.
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To access the LangCache API, you need:
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- LangCache API base URL
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- LangCache service API key
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- Cache ID
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When you call the API, you need to pass the LangCache API key in the `Authorization` header as a Bearer token and the Cache ID as the `cacheId` path parameter.
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For example, to check the health of the cache using `cURL`:
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```bash
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curl -s -X GET "https://$HOST/v1/caches/$CACHE_ID/health" \
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-H "accept: application/json" \
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-H "Authorization: Bearer $API_KEY"
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```
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- The example expects several variables to be set in the shell:
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- **$HOST** - the LangCache API base URL
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- **$CACHE_ID** - the Cache ID of your cache
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- **$API_KEY** - The LangCache API token
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{{% info %}}
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This example uses `cURL` and Linux shell scripts to demonstrate the API; you can use any standard REST client or library.
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{{% /info %}}
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You can also use the [LangCache SDKs](#langcache-sdk) for Javascript and Python to access the API.
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## API examples
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### Check cache health
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Use `GET /v1/caches/{cacheId}/health` to check the health of the cache.
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```sh
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GET https://[host]/v1/caches/{cacheId}/health
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```
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### Search LangCache for similar responses
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Use `POST /v1/caches/{cacheId}/entries/search` to search the cache for matching responses to a user prompt.
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```sh
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POST https://[host]/v1/caches/{cacheId}/entries/search
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{
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"prompt": "User prompt text"
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}
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```
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Place this call in your client app right before you call your LLM's REST API. If LangCache returns a response, you can send that response back to the user instead of calling the LLM.
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If LangCache does not return a response, you should call your LLM's REST API to generate a new response. After you get a response from the LLM, you can [store it in LangCache](#store-a-new-response-in-langcache) for future use.
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You can also scope the responses returned from LangCache by adding an `attributes` object to the request. LangCache will only return responses that match the attributes you specify.
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```sh
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POST https://[host]/v1/caches/{cacheId}/entries/search
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{
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"prompt": "User prompt text",
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"attributes": {
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"customAttributeName": "customAttributeValue"
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}
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}
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```
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### Store a new response in LangCache
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Use `POST /v1/caches/{cacheId}/entries` to store a new response in the cache.
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```sh
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POST https://[host]/v1/caches/{cacheId}/entries
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{
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"prompt": "User prompt text",
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"response": "LLM response text"
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}
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```
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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.
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You can also store the responses with custom attributes by adding an `attributes` object to the request.
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```sh
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POST https://[host]/v1/caches/{cacheId}/entries
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{
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"prompt": "User prompt text",
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"response": "LLM response text",
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"attributes": {
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"customAttributeName": "customAttributeValue"
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}
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}
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```
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### Delete cached responses
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Use `DELETE /v1/caches/{cacheId}/entries/{entryId}` to delete a cached response from the cache.
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You can also use `DELETE /v1/caches/{cacheId}/entries` to delete multiple cached responses at once. If you provide an `attributes` object, LangCache will delete all responses that match the attributes you specify.
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```sh
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DELETE https://[host]/v1/caches/{cacheId}/entries
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{
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"attributes": {
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"customAttributeName": "customAttributeValue"
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}
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}
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```
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## LangCache SDK
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If your app is written in Javascript or Python, you can also use the LangCache Software Development Kits (SDKs) to access the API.
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To learn how to use the LangCache SDKs:
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- [LangCache SDK for Javascript](https://www.npmjs.com/package/@redis-ai/langcache)
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- [LangCache SDK for Python](https://pypi.org/project/langcache/)
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Title: LangCache REST API
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linkTitle: API reference
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layout: apireference
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type: page
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params:
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sourcefile: ./api.yaml
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sortOperationsAlphabetically: false
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---

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