# rag-jaguardb This template performs RAG using JaguarDB and OpenAI. ## Environment Setup You should export two environment variables, one being your Jaguar URI, the other being your OpenAI API KEY. If you do not have JaguarDB set up, see the `Setup Jaguar` section at the bottom for instructions on how to do so. ```shell export JAGUAR_API_KEY=... export OPENAI_API_KEY=... ``` ## 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-jaguardb ``` If you want to add this to an existing project, you can just run: ```shell langchain app add rag-jagaurdb ``` And add the following code to your `server.py` file: ```python from rag_jaguardb import chain as rag_jaguardb add_routes(app, rag_jaguardb_chain, path="/rag-jaguardb") ``` (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/rag-jaguardb/playground](http://127.0.0.1:8000/rag-jaguardb/playground) We can access the template from code with: ```python from langserve.client import RemoteRunnable runnable = RemoteRunnable("http://localhost:8000/rag-jaguardb") ``` ## JaguarDB Setup To utilize JaguarDB, you can use docker pull and docker run commands to quickly setup JaguarDB. ```shell docker pull jaguardb/jaguardb docker run -d -p 8888:8888 --name jaguardb jaguardb/jaguardb ``` To launch the JaguarDB client terminal to interact with JaguarDB server: ```shell docker exec -it jaguardb /home/jaguar/jaguar/bin/jag ``` Another option is to download an already-built binary package of JaguarDB on Linux, and deploy the database on a single node or in a cluster of nodes. The streamlined process enables you to quickly start using JaguarDB and leverage its powerful features and functionalities. [here](http://www.jaguardb.com/download.html).