mirror of
https://github.com/hwchase17/langchain
synced 2024-11-08 07:10:35 +00:00
71 lines
2.3 KiB
Markdown
71 lines
2.3 KiB
Markdown
# Hybrid Search in Weaviate
|
|
This template shows you how to use the hybrid search feature in Weaviate. Hybrid search combines multiple search algorithms to improve the accuracy and relevance of search results.
|
|
|
|
Weaviate uses both sparse and dense vectors to represent the meaning and context of search queries and documents. The results use a combination of `bm25` and vector search ranking to return the top results.
|
|
|
|
## Configurations
|
|
Connect to your hosted Weaviate Vectorstore by setting a few env variables in `chain.py`:
|
|
|
|
* `WEAVIATE_ENVIRONMENT`
|
|
* `WEAVIATE_API_KEY`
|
|
|
|
You will also need to set your `OPENAI_API_KEY` to use the OpenAI models.
|
|
|
|
## Get Started
|
|
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 hybrid-search-weaviate
|
|
```
|
|
|
|
If you want to add this to an existing project, you can just run:
|
|
|
|
```shell
|
|
langchain app add hybrid-search-weaviate
|
|
```
|
|
|
|
And add the following code to your `server.py` file:
|
|
```python
|
|
from hybrid_search_weaviate import chain as hybrid_search_weaviate_chain
|
|
|
|
add_routes(app, hybrid_search_weaviate_chain, path="/hybrid-search-weaviate")
|
|
```
|
|
|
|
(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/hybrid-search-weaviate/playground](http://127.0.0.1:8000/hybrid-search-weaviate/playground)
|
|
|
|
We can access the template from code with:
|
|
|
|
```python
|
|
from langserve.client import RemoteRunnable
|
|
|
|
runnable = RemoteRunnable("http://localhost:8000/hybrid-search-weaviate")
|
|
```
|