Quickest way to test naive RAG run with AutoRAG.
Chat about images by uploading them and typing questions
Interact with a chatbot that searches for information and reasons based on your queries
Interact with NCTC OSINT Agent for OSINT tasks
Engage in conversations with a smart AI assistant
Engage in conversations with a multilingual language model
Run Llama,Qwen,Gemma,Mistral, any warm/cold LLM. No GPU req.
Uncesored
Send messages to a WhatsApp-style chatbot
This is open-o1 demo with improved system prompt
Generate text chat conversations using images and text prompts
Generate responses and perform tasks using AI
Generate text responses in a chat interface
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.