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Add hybrid search alpha parameter to the docs (#3397)

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Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
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Erika Shorten
2025-08-27 10:36:39 -04:00
committed by GitHub
parent fc3f2c49d2
commit 92b70e652d
1 changed files with 7 additions and 2 deletions
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9
docs/en/tools/database-data/weaviatevectorsearchtool.mdx
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@@ -1,13 +1,13 @@
---
title: Weaviate Vector Search
description: The `WeaviateVectorSearchTool` is designed to search a Weaviate vector database for semantically similar documents.
description: The `WeaviateVectorSearchTool` is designed to search a Weaviate vector database for semantically similar documents using hybrid search.
icon: network-wired
---
## Overview
The `WeaviateVectorSearchTool` is specifically crafted for conducting semantic searches within documents stored in a Weaviate vector database. This tool allows you to find semantically similar documents to a given query, leveraging the power of vector embeddings for more accurate and contextually relevant search results.
The `WeaviateVectorSearchTool` is specifically crafted for conducting semantic searches within documents stored in a Weaviate vector database. This tool allows you to find semantically similar documents to a given query, leveraging the power of vector and keyword search for more accurate and contextually relevant search results.
[Weaviate](https://weaviate.io/) is a vector database that stores and queries vector embeddings, enabling semantic search capabilities.
@@ -39,6 +39,7 @@ from crewai_tools import WeaviateVectorSearchTool
tool = WeaviateVectorSearchTool(
collection_name='example_collections',
limit=3,
alpha=0.75,
weaviate_cluster_url="https://your-weaviate-cluster-url.com",
weaviate_api_key="your-weaviate-api-key",
)
@@ -63,6 +64,7 @@ The `WeaviateVectorSearchTool` accepts the following parameters:
- **weaviate_cluster_url**: Required. The URL of the Weaviate cluster.
- **weaviate_api_key**: Required. The API key for the Weaviate cluster.
- **limit**: Optional. The number of results to return. Default is `3`.
- **alpha**: Optional. Controls the weighting between vector and keyword (BM25) search. alpha = 0 -> BM25 only, alpha = 1 -> vector search only. Default is `0.75`.
- **vectorizer**: Optional. The vectorizer to use. If not provided, it will use `text2vec_openai` with the `nomic-embed-text` model.
- **generative_model**: Optional. The generative model to use. If not provided, it will use OpenAI's `gpt-4o`.
@@ -78,6 +80,7 @@ from weaviate.classes.config import Configure
tool = WeaviateVectorSearchTool(
collection_name='example_collections',
limit=3,
alpha=0.75,
vectorizer=Configure.Vectorizer.text2vec_openai(model="nomic-embed-text"),
generative_model=Configure.Generative.openai(model="gpt-4o-mini"),
weaviate_cluster_url="https://your-weaviate-cluster-url.com",
@@ -128,6 +131,7 @@ with test_docs.batch.dynamic() as batch:
tool = WeaviateVectorSearchTool(
collection_name='example_collections',
limit=3,
alpha=0.75,
weaviate_cluster_url="https://your-weaviate-cluster-url.com",
weaviate_api_key="your-weaviate-api-key",
)
@@ -145,6 +149,7 @@ from crewai_tools import WeaviateVectorSearchTool
weaviate_tool = WeaviateVectorSearchTool(
collection_name='example_collections',
limit=3,
alpha=0.75,
weaviate_cluster_url="https://your-weaviate-cluster-url.com",
weaviate_api_key="your-weaviate-api-key",
)