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# 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.
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You can sign up for LangSmith [here ](https://smith.langchain.com/ ).
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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/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 ).
