Readme rewrite (#12615)

Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>

templates/guardrails-output-parser/README.md

@@ -1,9 +1,73 @@
+
 # guardrails-output-parser
 
-Uses [guardrails-ai](https://github.com/guardrails-ai/guardrails) to validate output.
+This template uses [guardrails-ai](https://github.com/guardrails-ai/guardrails) to validate LLM output. 
 
-This example protects against profanity, but with Guardrails you can protect against a multitude of things.
+The `GuardrailsOutputParser` is set in `chain.py`.
+ 
+The default example protects against profanity.
 
-If Guardrails does not find any profanity, then the translated output is returned as is.
+## Environment Setup
 
-If Guardrails does find profanity, then an empty string is returned.
+Set the `OPENAI_API_KEY` environment variable to access the OpenAI models.
+
+## Usage
+
+To use this package, you should first have the LangChain CLI installed:
+
+```shell
+pip install -U "langchain-cli[serve]"
+```
+
+To create a new LangChain project and install this as the only package, you can do:
+
+```shell
+langchain app new my-app --package guardrails-output-parser
+```
+
+If you want to add this to an existing project, you can just run:
+
+```shell
+langchain app add guardrails-output-parser
+```
+
+And add the following code to your `server.py` file:
+```python
+from guardrails_output_parser import chain as guardrails_output_parser_chain
+
+add_routes(app, guardrails_output_parser_chain, path="/guardrails-output-parser")
+```
+
+(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
+
+
+```shell
+export LANGCHAIN_TRACING_V2=true
+export LANGCHAIN_API_KEY=<your-api-key>
+export LANGCHAIN_PROJECT=<your-project>  # if not specified, defaults to "default"
+```
+
+If you are inside this directory, then you can spin up a LangServe instance directly by:
+
+```shell
+langchain serve
+```
+
+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/guardrails-output-parser/playground](http://127.0.0.1:8000/guardrails-output-parser/playground)  
+
+We can access the template from code with:
+
+```python
+from langserve.client import RemoteRunnable
+
+runnable = RemoteRunnable("http://localhost:8000/guardrails-output-parser")
+```
+
+If Guardrails does not find any profanity, then the translated output is returned as is. If Guardrails does find profanity, then an empty string is returned.

templates/guardrails-output-parser/pyproject.toml

@@ -1,5 +1,5 @@
 [tool.poetry]
-name = "guardrails_output_parser"
+name = "guardrails-output-parser"
 version = "0.0.1"
 description = ""
 authors = []