AutoRAG Optimization Web UI
Meta-Llama-3.1-8B-Instruct
Communicate with a multimodal chatbot
Example on using Langfuse to trace Gradio applications.
Generate text based on user prompts
Chat with a conversational AI
Chat Long COT model that uses tags
Communicate with an AI assistant and convert text to speech
Engage in conversations with a multilingual language model
Implement Gemini2 Flash Thinking model with Gradio
Engage in conversation with GPT-4o Mini
Uncesored
Generate text chat conversations using images and text prompts
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.