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75 lines
2.7 KiB
Plaintext
75 lines
2.7 KiB
Plaintext
---
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title: YouTube Channel RAG Search
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description: The `YoutubeChannelSearchTool` is designed to perform a RAG (Retrieval-Augmented Generation) search within the content of a Youtube channel.
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icon: youtube
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---
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# `YoutubeChannelSearchTool`
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<Note>
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We are still working on improving tools, so there might be unexpected behavior or changes in the future.
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</Note>
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## Description
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This tool is designed to perform semantic searches within a specific Youtube channel's content.
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Leveraging the RAG (Retrieval-Augmented Generation) methodology, it provides relevant search results,
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making it invaluable for extracting information or finding specific content without the need to manually sift through videos.
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It streamlines the search process within Youtube channels, catering to researchers, content creators, and viewers seeking specific information or topics.
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## Installation
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To utilize the YoutubeChannelSearchTool, the `crewai_tools` package must be installed. Execute the following command in your shell to install:
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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 begin using the YoutubeChannelSearchTool, follow the example below.
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This demonstrates initializing the tool with a specific Youtube channel handle and conducting a search within that channel's content.
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```python Code
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from crewai_tools import YoutubeChannelSearchTool
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# Initialize the tool to search within any Youtube channel's content the agent learns about during its execution
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tool = YoutubeChannelSearchTool()
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# OR
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# Initialize the tool with a specific Youtube channel handle to target your search
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tool = YoutubeChannelSearchTool(youtube_channel_handle='@exampleChannel')
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```
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## Arguments
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- `youtube_channel_handle` : A mandatory string representing the Youtube channel handle. This parameter is crucial for initializing the tool to specify the channel you want to search within. The tool is designed to only search within the content of the provided channel handle.
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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 Code
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tool = YoutubeChannelSearchTool(
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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", # or openai, ollama, ...
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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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``` |