mirror of
https://github.com/hwchase17/langchain
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71 lines
2.3 KiB
Markdown
71 lines
2.3 KiB
Markdown
# Hybrid Search in Weaviate
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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.
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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.
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## Configurations
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Connect to your hosted Weaviate Vectorstore by setting a few env variables in `chain.py`:
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* `WEAVIATE_ENVIRONMENT`
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* `WEAVIATE_API_KEY`
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You will also need to set your `OPENAI_API_KEY` to use the OpenAI models.
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## Get Started
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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 hybrid-search-weaviate
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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 hybrid-search-weaviate
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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 hybrid_search_weaviate import chain as hybrid_search_weaviate_chain
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add_routes(app, hybrid_search_weaviate_chain, path="/hybrid-search-weaviate")
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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/hybrid-search-weaviate/playground](http://127.0.0.1:8000/hybrid-search-weaviate/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/hybrid-search-weaviate")
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```
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