Add rag google vertex ai search template (langchain-ai#13294)

- **Description:** This is a template demonstrating how to utilize
Google Vertex AI Search in conjunction with ChatVertexAI()

templates/rag-google-cloud-vertexai-search/LICENSE

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+MIT License
+
+Copyright (c) 2023 LangChain, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

templates/rag-google-cloud-vertexai-search/README.md

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+# rag-google-cloud-vertexai-search
+
+This template is an application that utilizes Google Vertex AI Search, a machine learning powered search service, and
+PaLM 2 for Chat (chat-bison). The application uses a Retrieval chain to answer questions based on your documents.
+
+For more context on building RAG applications with Vertex AI Search,
+check [here](https://cloud.google.com/generative-ai-app-builder/docs/enterprise-search-introduction).
+
+## Environment Setup
+
+Before using this template, please ensure that you are authenticated with Vertex AI Search. See the authentication
+guide: [here](https://cloud.google.com/generative-ai-app-builder/docs/authentication).
+
+You will also need to create:
+
+- A search application [here](https://cloud.google.com/generative-ai-app-builder/docs/create-engine-es)
+- A data store [here](https://cloud.google.com/generative-ai-app-builder/docs/create-data-store-es)
+
+A suitable dataset to test this template with is the Alphabet Earnings Reports, which you can
+find [here](https://abc.xyz/investor/). The data is also available
+at `gs://cloud-samples-data/gen-app-builder/search/alphabet-investor-pdfs`.
+
+Set the following environment variables:
+
+* `GOOGLE_CLOUD_PROJECT_ID` - Your Google Cloud project ID.
+* `DATA_STORE_ID` - The ID of the data store in Vertex AI Search, which is a 36-character alphanumeric value found on
+  the data store details page.
+* `MODEL_TYPE` - The model type for Vertex AI Search.
+
+## 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 rag-google-cloud-vertexai-search
+```
+
+If you want to add this to an existing project, you can just run:
+
+```shell
+langchain app add rag-google-cloud-vertexai-search
+```
+
+And add the following code to your `server.py` file:
+
+```python
+from rag_google_cloud_vertexai_search.chain import chain as rag_google_cloud_vertexai_search_chain
+
+add_routes(app, rag_google_cloud_vertexai_search_chain, path="/rag-google-cloud-vertexai-search")
+```
+
+(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 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-google-cloud-vertexai-search/playground](http://127.0.0.1:8000/rag-google-cloud-vertexai-search/playground)
+
+We can access the template from code with:
+
+```python
+from langserve.client import RemoteRunnable
+
+runnable = RemoteRunnable("http://localhost:8000/rag-google-cloud-vertexai-search")
+```

templates/rag-google-cloud-vertexai-search/main.py

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+from rag_google_cloud_vertexai_search.chain import chain
+
+if __name__ == "__main__":
+    query = "Who is the CEO of Google Cloud?"
+    print(chain.invoke(query))