Quickest way to test naive RAG run with AutoRAG.
Send messages to a WhatsApp-style chatbot
Generate responses and perform tasks using AI
Chat with Qwen, a helpful assistant
Example on using Langfuse to trace Gradio applications.
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Generate detailed, refined responses to user queries
Generate text responses in a chat interface
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Qwen-2.5-72B on serverless inference
The Naive RAG Chatbot is a simple yet effective tool designed to test naive RAG (Retrieval-Augmented Generation) implementations. It allows users to upload files and interact with a document-aware AI assistant, making it an excellent choice for quick experimentation and prototyping.
• Document Upload: Easily upload files to train the AI on specific content.
• Document Awareness: The chatbot remembers and can reference uploaded documents during conversations.
• User-Friendly Interface: Intuitive design for seamless interaction with the AI.
• Integration with AutoRAG: Built-in support for AutoRAG, enabling robust retrieval and generation capabilities.
• Real-Time Responses: Get instant answers to your questions based on the uploaded documents.
• Versatile File Support: Accepts multiple file formats for flexibility in training data.
What file formats does Naive RAG Chatbot support?
The chatbot supports multiple file formats, including PDF, TXT, and DOC, ensuring flexibility in training data.
Can I use Naive RAG Chatbot for real-world applications?
While it's primarily designed for testing and prototyping, it can be adapted for lightweight real-world applications with document-aware AI needs.
How does it differ from traditional chatbots?
Naive RAG Chatbot stands out by leveraging uploaded documents to provide context-aware responses, unlike traditional chatbots that rely on predefined knowledge or internet access.