# Vertex AI - Chuck Norris This template makes jokes about Chuck Norris using `Google Cloud Vertex AI PaLM2`. ## Environment Setup First, make sure you have a Google Cloud project with an active billing account, and have the [gcloud CLI installed](https://cloud.google.com/sdk/docs/install). Configure [application default credentials](https://cloud.google.com/docs/authentication/provide-credentials-adc): ```shell gcloud auth application-default login ``` To set a default Google Cloud project to use, run this command and set [the project ID](https://support.google.com/googleapi/answer/7014113?hl=en) of the project you want to use: ```shell gcloud config set project [PROJECT-ID] ``` Enable the [Vertex AI API](https://console.cloud.google.com/apis/library/aiplatform.googleapis.com) for the project: ```shell gcloud services enable aiplatform.googleapis.com ``` ## Usage To use this package, you should first have the LangChain CLI installed: ```shell pip install -U langchain-cli ``` To create a new LangChain project and install this as the only package, you can do: ```shell langchain app new my-app --package pirate-speak ``` If you want to add this to an existing project, you can just run: ```shell langchain app add vertexai-chuck-norris ``` And add the following code to your `server.py` file: ```python from vertexai_chuck_norris.chain import chain as vertexai_chuck_norris_chain add_routes(app, vertexai_chuck_norris_chain, path="/vertexai-chuck-norris") ``` (Optional) Let's now configure LangSmith. LangSmith will help us trace, monitor and debug LangChain applications. You can sign up for LangSmith [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= export LANGCHAIN_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/vertexai-chuck-norris/playground](http://127.0.0.1:8000/vertexai-chuck-norris/playground) We can access the template from code with: ```python from langserve.client import RemoteRunnable runnable = RemoteRunnable("http://localhost:8000/vertexai-chuck-norris") ```