AutoRAG Optimization Web UI
Chat with different models using various approaches
Generate chat responses using Llama-2 13B model
Discover chat prompts with a searchable map
Engage in chat with Llama-2 7B model
Generate chat responses with Qwen AI
Generate answers from uploaded PDF
Generate human-like text responses in conversation
mistralai/Mistral-7B-Instruct-v0.3
Select and chat with various advanced language models
Example on using Langfuse to trace Gradio applications.
Quickest way to test naive RAG run with AutoRAG.
Generate responses using text and images
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.