# Hybrid search - Weaviate

This template shows you how to use the hybrid search feature in `Weaviate` vector store.
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. 
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=<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")
```