AutoRAG Optimization Web UI
Generate conversational responses to text input
Qwen-2.5-72B on serverless inference
Create and manage OpenAI assistants for chat
Chat with different models using various approaches
Ask legal questions to get expert answers
mistralai/Mistral-7B-Instruct-v0.3
Chat with images and text
Discover chat prompts with a searchable map
Implement Gemini2 Flash Thinking model with Gradio
Communicate with a multimodal chatbot
Quickest way to test naive RAG run with AutoRAG.
Run Llama,Qwen,Gemma,Mistral, any warm/cold LLM. No GPU req.
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.