Quickest way to test naive RAG run with AutoRAG.
Communicate with a multimodal chatbot
Generate responses and perform tasks using AI
Run Llama,Qwen,Gemma,Mistral, any warm/cold LLM. No GPU req.
Send messages to a WhatsApp-style chatbot
Start a debate with AI assistants
Generate text based on user prompts
Generate conversational responses using text input
Chat with a Japanese language model
Chat with a Qwen AI assistant
Marin kitagawa an AI chatbot
Vision Chatbot with ImgGen & Web Search - Runs on CPU
Implement Gemini2 Flash Thinking model with Gradio
The Naive RAG Chatbot is a specialized AI-powered chatbot designed to quickly test and implement Retrieval-Augmented Generation (RAG) systems. It allows users to interact with a document-aware AI assistant by simply uploading files and engaging in conversation. This tool is ideal for those looking to efficiently explore RAG capabilities without complex setups, making it a straightforward solution for testing and development.
• Document Upload: Easily upload files for the AI to reference during conversations.
• Context-Aware Responses: The chatbot uses the uploaded documents to provide accurate and relevant answers.
• Simple Integration: Works seamlessly with AutoRAG, enabling quick deployment of RAG workflows.
• File Type Support: Accepts multiple file formats for document upload.
• User-Friendly Interface: Designed for ease of use, with a focus on simplicity and efficiency.
What does RAG stand for?
RAG stands for Retrieval-Augmented Generation, a technology that combines document retrieval with AI generation to improve response accuracy.
What file types are supported?
The Naive RAG Chatbot supports PDF, TXT, DOCX, and JSON formats for document uploads.
Is there a limit to document size?
Yes, documents should be under 50MB to ensure optimal performance.