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58 lines
2.2 KiB
Markdown
58 lines
2.2 KiB
Markdown
# WebsiteSearchTool
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## Description
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This tool is specifically crafted for conducting semantic searches within the content of a particular website. Leveraging a Retrieval-Augmented Generation (RAG) model, it navigates through the information provided on a given URL. Users have the flexibility to either initiate a search across any website known or discovered during its usage or to concentrate the search on a predefined, specific website.
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## Installation
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Install the crewai_tools package by executing the following command in your terminal:
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```shell
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pip install 'crewai[tools]'
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```
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## Example
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To utilize the WebsiteSearchTool for different use cases, follow these examples:
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```python
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from crewai_tools import WebsiteSearchTool
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# To enable the tool to search any website the agent comes across or learns about during its operation
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tool = WebsiteSearchTool()
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# OR
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# To restrict the tool to only search within the content of a specific website.
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tool = WebsiteSearchTool(website='https://example.com')
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```
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## Arguments
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- `website` : An optional argument that specifies the valid website URL to perform the search on. This becomes necessary if the tool is initialized without a specific website. In the `WebsiteSearchToolSchema`, this argument is mandatory. However, in the `FixedWebsiteSearchToolSchema`, it becomes optional if a website is provided during the tool's initialization, as it will then only search within the predefined website's content.
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## Custom model and embeddings
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By default, the tool uses OpenAI for both embeddings and summarization. To customize the model, you can use a config dictionary as follows:
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```python
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tool = WebsiteSearchTool(
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config=dict(
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llm=dict(
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provider="ollama", # or google, openai, anthropic, llama2, ...
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config=dict(
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model="llama2",
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# temperature=0.5,
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# top_p=1,
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# stream=true,
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),
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),
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embedder=dict(
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provider="google",
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config=dict(
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model="models/embedding-001",
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task_type="retrieval_document",
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# title="Embeddings",
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),
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),
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)
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)
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```
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