mirror of
https://github.com/hwchase17/langchain
synced 2024-11-06 03:20:49 +00:00
91 lines
2.6 KiB
Markdown
91 lines
2.6 KiB
Markdown
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# rag-jaguardb
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This template performs RAG using JaguarDB and OpenAI.
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## Environment Setup
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You should export two environment variables, one being your Jaguar URI, the other being your OpenAI API KEY.
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If you do not have JaguarDB set up, see the `Setup Jaguar` section at the bottom for instructions on how to do so.
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```shell
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export JAGUAR_API_KEY=...
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export OPENAI_API_KEY=...
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```
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## Usage
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To use this package, you should first have the LangChain CLI installed:
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```shell
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pip install -U langchain-cli
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```
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To create a new LangChain project and install this as the only package, you can do:
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```shell
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langchain app new my-app --package rag-jaguardb
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```
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If you want to add this to an existing project, you can just run:
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```shell
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langchain app add rag-jagaurdb
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```
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And add the following code to your `server.py` file:
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```python
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from rag_jaguardb import chain as rag_jaguardb
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add_routes(app, rag_jaguardb_chain, path="/rag-jaguardb")
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```
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(Optional) Let's now configure LangSmith.
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LangSmith will help us trace, monitor and debug LangChain applications.
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LangSmith is currently in private beta, you can sign up [here](https://smith.langchain.com/).
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If you don't have access, you can skip this section
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```shell
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export LANGCHAIN_TRACING_V2=true
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export LANGCHAIN_API_KEY=<your-api-key>
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export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"
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```
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If you are inside this directory, then you can spin up a LangServe instance directly by:
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```shell
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langchain serve
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```
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This will start the FastAPI app with a server is running locally at
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[http://localhost:8000](http://localhost:8000)
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We can see all templates at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
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We can access the playground at [http://127.0.0.1:8000/rag-jaguardb/playground](http://127.0.0.1:8000/rag-jaguardb/playground)
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We can access the template from code with:
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```python
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from langserve.client import RemoteRunnable
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runnable = RemoteRunnable("http://localhost:8000/rag-jaguardb")
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```
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## JaguarDB Setup
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To utilize JaguarDB, you can use docker pull and docker run commands to quickly setup JaguarDB.
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```shell
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docker pull jaguardb/jaguardb
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docker run -d -p 8888:8888 --name jaguardb jaguardb/jaguardb
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```
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To launch the JaguarDB client terminal to interact with JaguarDB server:
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```shell
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docker exec -it jaguardb /home/jaguar/jaguar/bin/jag
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```
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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).
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