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Rag Gpt

RAG-GPT, leveraging LLM and RAG technology, learns from user-customized knowledge bases to provide contextually relevant answers for a wide range of queries, ensuring rapid and accurate information retrieval.

Rag Gpt

RAG-GPT, leveraging LLM and RAG technology, learns from user-customized knowledge bases to provide contextually relevant answers for a wide range of queries, ensuring rapid and accurate information retrieval.

Author Avatar Theme by gpt-open
Github Stars Github Stars: 478
Last Commit Last Commit: Jul 19, 2024 -
First Commit Created: Jan 17, 2026 -
Rag Gpt screenshot

Overview

RAG-GPT is a robust solution for deploying a conversational service robot with built-in support for various language models. Whether you’re looking to utilize cloud-based options or prefer local processing, RAG-GPT provides a flexible architecture that ensures your chatbot is ready to engage with users effectively. The installation process is designed to be user-friendly, making it an appealing choice for developers looking to get started quickly.

With the capability to integrate diverse knowledge bases and a customizable backend, RAG-GPT is well-suited for both new and experienced users. Once set up, the service enables an attractive user interface and an efficient management dashboard, ensuring a seamless experience from both administrator and user perspectives.

Features

  • Built-in LLM Support: Easily switch between cloud-based language learning models (LLMs) like OpenAI and ZhipuAI or utilize local LLMs without hassle.

  • Quick Setup: Achieve a production-level conversational service in just five minutes, allowing for rapid deployment without a steep learning curve.

  • Diverse Knowledge Base Integration: Import data from various sources, including websites, isolated URLs, and local files, to enrich the chatbot’s responses.

  • Flexible Configuration: The user-friendly backend offers customizable settings, which streamline management and tailor the experience to specific needs.

  • Attractive UI: The visually appealing interface can be personalized, providing a pleasant user experience for both administrators and end-users.

  • User-Friendly Admin Console: Manage and monitor chatbot functionality, including user requests and data management, all from a centralized dashboard.

  • Testing Capabilities: Built-in features allow for easy testing of the chatbot before deployment, ensuring optimal performance and user satisfaction.