RAGs, an application by Streamlit, simplifies GPT pipeline creation and deployment with an intuitive interface. The latest version, RAGs v2, enhances user experience with features for building and customizing ChatGPTs, managing RAG pipelines, and supporting multiple large language models. To use it, install with ‘pip,’ create pipelines, deploy, and query via command line. It’s a valuable tool for NLP challenges, with resources available on GitHub and Streamlit community platforms.
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Introducing RAGs: Your AI-Powered NLP Solution
RAGs simplifies the creation and deployment of GPT pipelines for natural language processing (NLP) tasks. With RAGs, you can easily specify your requirements and let the app handle the complex coding.
What’s New in RAGs v2?
The latest version, RAGs v2, is a major improvement, providing a more flexible and user-friendly platform for developing ChatGPTs. It allows you to:
- Create, save, and manage multiple pipelines
- Customize pipelines with different data sets or prompts
- Delete pipelines you no longer need
- Improve development with linting and CI tools
- Support for a variety of Large Language Models (LLMs)
- Load files or web pages for extended functionality
Check out the explanatory video for a quick start guide on using RAGs v2.
Main Sections of RAGs
- Home Page: Instruct the “builder agent” to construct your RAG pipeline.
- RAG Config Section: View and edit the settings created by the builder agent.
- Chatbot Interface: Interact with the RAG agent and ask questions based on your data.
How to Use RAGs
Follow these steps to get started:
- Install RAGs with the command:
pip install rags - Create a pipeline:
rags create-pipeline - Deploy your pipeline:
rags deploy - Query your pipeline:
rags query
Summary: Elevate Your NLP Capabilities with RAGs
RAGs is an essential tool for anyone looking to tackle NLP challenges with GPTs. It’s designed to be intuitive and efficient, making AI integration into your business seamless.
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List of Useful Links:
- AI Lab in Telegram @aiscrumbot – free consultation
- Meet RAGs: A Streamlit App that Lets You Create a RAG Pipeline from a Data Source Using Natural Language
- MarkTechPost
- Twitter – @itinaicom
