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62 lines
1.9 KiB
Markdown
62 lines
1.9 KiB
Markdown
# RagTool: A Dynamic Knowledge Base Tool
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RagTool is designed to answer questions by leveraging the power of RAG by leveraging (EmbedChain). It integrates seamlessly with the CrewAI ecosystem, offering a versatile and powerful solution for information retrieval.
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## **Overview**
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RagTool enables users to dynamically query a knowledge base, making it an ideal tool for applications requiring access to a vast array of information. Its flexible design allows for integration with various data sources, including files, directories, web pages, yoututbe videos and custom configurations.
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## **Usage**
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RagTool can be instantiated with data from different sources, including:
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- 📰 PDF file
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- 📊 CSV file
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- 📃 JSON file
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- 📝 Text
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- 📁 Directory/ Folder
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- 🌐 HTML Web page
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- 📽️ Youtube Channel
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- 📺 Youtube Video
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- 📚 Docs website
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- 📝 MDX file
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- 📄 DOCX file
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- 🧾 XML file
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- 📬 Gmail
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- 📝 Github
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- 🐘 Postgres
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- 🐬 MySQL
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- 🤖 Slack
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- 💬 Discord
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- 🗨️ Discourse
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- 📝 Substack
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- 🐝 Beehiiv
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- 💾 Dropbox
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- 🖼️ Image
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- ⚙️ Custom
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#### **Creating an Instance**
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```python
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from crewai_tools.tools.rag_tool import RagTool
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# Example: Loading from a file
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rag_tool = RagTool().from_file('path/to/your/file.txt')
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# Example: Loading from a directory
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rag_tool = RagTool().from_directory('path/to/your/directory')
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# Example: Loading from a web page
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rag_tool = RagTool().from_web_page('https://example.com')
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```
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## **Contribution**
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Contributions to RagTool and the broader CrewAI tools ecosystem are welcome. To contribute, please follow the standard GitHub workflow for forking the repository, making changes, and submitting a pull request.
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## **License**
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RagTool is open-source and available under the MIT license.
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Thank you for considering RagTool for your knowledge base needs. Your contributions and feedback are invaluable to making RagTool even better.
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