mirror of
https://github.com/hwchase17/langchain
synced 2024-11-18 09:25:54 +00:00
82 lines
2.5 KiB
Markdown
82 lines
2.5 KiB
Markdown
# rag-opensearch
|
|
|
|
This Template performs RAG using [OpenSearch](https://python.langchain.com/docs/integrations/vectorstores/opensearch).
|
|
|
|
## Environment Setup
|
|
|
|
Set the following environment variables.
|
|
|
|
- `OPENAI_API_KEY` - To access OpenAI Embeddings and Models.
|
|
|
|
And optionally set the OpenSearch ones if not using defaults:
|
|
|
|
- `OPENSEARCH_URL` - URL of the hosted OpenSearch Instance
|
|
- `OPENSEARCH_USERNAME` - User name for the OpenSearch instance
|
|
- `OPENSEARCH_PASSWORD` - Password for the OpenSearch instance
|
|
- `OPENSEARCH_INDEX_NAME` - Name of the index
|
|
|
|
To run the default OpenSeach instance in docker, you can use the command
|
|
```shell
|
|
docker run -p 9200:9200 -p 9600:9600 -e "discovery.type=single-node" --name opensearch-node -d opensearchproject/opensearch:latest
|
|
```
|
|
|
|
Note: To load dummy index named `langchain-test` with dummy documents, run `python dummy_index_setup.py` in the package
|
|
|
|
## 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-opensearch
|
|
```
|
|
|
|
If you want to add this to an existing project, you can just run:
|
|
|
|
```shell
|
|
langchain app add rag-opensearch
|
|
```
|
|
|
|
And add the following code to your `server.py` file:
|
|
```python
|
|
from rag_opensearch import chain as rag_opensearch_chain
|
|
|
|
add_routes(app, rag_opensearch_chain, path="/rag-opensearch")
|
|
```
|
|
|
|
(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 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-opensearch/playground](http://127.0.0.1:8000/rag-opensearch/playground)
|
|
|
|
We can access the template from code with:
|
|
|
|
```python
|
|
from langserve.client import RemoteRunnable
|
|
|
|
runnable = RemoteRunnable("http://localhost:8000/rag-opensearch")
|
|
``` |