templates[patch]: Rag redis template dependency update (#13614)

- **Description:** Update RAG Redis template readme and dependencies.

templates/rag-redis/README.md

@@ -1,15 +1,19 @@
 
 # rag-redis
 
-This template performs RAG using Redis and OpenAI on financial 10k filings docs (for Nike). 
+This template performs RAG using Redis (vector database) and OpenAI (LLM) on financial 10k filings docs for Nike.
 
 It relies on the sentence transformer `all-MiniLM-L6-v2` for embedding chunks of the pdf and user questions.
 
 ## Environment Setup
 
-Set the `OPENAI_API_KEY` environment variable to access the OpenAI models.
+Set the `OPENAI_API_KEY` environment variable to access the [OpenAI](https://platform.openai.com) models:
 
-The following Redis environment variables need to be set:
+```bash
+export OPENAI_API_KEY= <YOUR OPENAI API KEY>
+```
+
+Set the following [Redis](https://redis.com/try-free) environment variables:
 
 ```bash
 export REDIS_HOST = <YOUR REDIS HOST>
@@ -33,10 +37,10 @@ We use a variety of environment variables to configure this application
 
 ## Usage
 
-To use this package, you should first have the LangChain CLI installed:
+To use this package, you should first have the LangChain CLI and Pydantic installed in a Python virtual environment:
 
 ```shell
-pip install -U langchain-cli
+pip install -U langchain-cli pydantic==1.10.13
 ```
 
 To create a new LangChain project and install this as the only package, you can do:
@@ -46,21 +50,20 @@ langchain app new my-app --package rag-redis
 ```
 
 If you want to add this to an existing project, you can just run:
-
 ```shell
 langchain app add rag-redis
 ```
 
-And add the following code to your `server.py` file:
+And add the following code snippet to your `app/server.py` file:
 ```python
 from rag_redis.chain import chain as rag_redis_chain
 
 add_routes(app, rag_redis_chain, path="/rag-redis")
 ```
 
-(Optional) Let's now configure LangSmith. 
-LangSmith will help us trace, monitor and debug LangChain applications. 
-LangSmith is currently in private beta, you can sign up [here](https://smith.langchain.com/). 
+(Optional) Let's now configure LangSmith.
+LangSmith will help us trace, monitor and debug LangChain applications.
+LangSmith is currently in private beta, you can sign up [here](https://smith.langchain.com/).
 If you don't have access, you can skip this section
 
 
@@ -76,11 +79,11 @@ If you are inside this directory, then you can spin up a LangServe instance dire
 langchain serve
 ```
 
-This will start the FastAPI app with a server is running locally at 
+This will start the FastAPI app with a server is running locally at
 [http://localhost:8000](http://localhost:8000)
 
 We can see all templates at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
-We can access the playground at [http://127.0.0.1:8000/rag-redis/playground](http://127.0.0.1:8000/rag-redis/playground)  
+We can access the playground at [http://127.0.0.1:8000/rag-redis/playground](http://127.0.0.1:8000/rag-redis/playground)
 
 We can access the template from code with:
 

templates/rag-redis/pyproject.toml

@@ -36,7 +36,7 @@ export_attr = "chain"
 [tool.templates-hub]
 use-case = "rag"
 author = "Redis"
-integrations = ["OpenAI", "Redis"]
+integrations = ["OpenAI", "Redis", "HuggingFace"]
 tags = ["vectordbs"]
 
 [tool.poe.tasks.start]