AutoRAG Optimization Web UI
Engage in conversations with a multilingual language model
Generate detailed step-by-step answers to questions
Communicate with an AI assistant and convert text to speech
Generate conversational responses using text input
Interact with a chatbot that searches for information and reasons based on your queries
Chat with a Japanese language model
Quickest way to test naive RAG run with AutoRAG.
Google Gemini Playground | ReffidGPT Chat
mistralai/Mistral-7B-Instruct-v0.3
llama.cpp server hosting a reasoning model CPU only.
Chat with a helpful AI assistant in Chinese
Fast and free uncensored chatbot that just works.
RAG Pipeline Optimization is a powerful tool designed to optimize and compare RAG (Retrieval-Augmented Generation) chat models. It provides an intuitive interface to streamline the process of running and evaluating RAG models using YAML and Parquet files. As part of the AutoRAG Optimization Web UI, this tool helps users refine their pipelines for better performance and accuracy.
What file formats does RAG Pipeline Optimization support?
RAG Pipeline Optimization supports YAML for configuration and Parquet for data handling and analysis.
How do I get started with RAG Pipeline Optimization?
Start by installing the AutoRAG Optimization Web UI, preparing your YAML and Parquet files, and following the step-by-step instructions in the interface.
Can I use RAG Pipeline Optimization for both small and large-scale models?
Yes, RAG Pipeline Optimization is designed to handle both small and large-scale RAG models, making it versatile for different use cases.