AutoRAG Optimization Web UI
Interact with an AI therapist that analyzes text and voice emotions, and responds with text-to-speech
Generate text responses in a chat interface
Chat with different models using various approaches
Chat with images and text
Example on using Langfuse to trace Gradio applications.
ChatBot Qwen
Generate text based on user prompts
Chat with Qwen2-72B-instruct using a system prompt
Engage in conversation with GPT-4o Mini
Fast and free uncensored chatbot that just works.
Generate chat responses with Qwen AI
Engage in chat with Llama-2 7B model
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.