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Bolnee-Chat Offers Self-Hosted RAG Chatbot Integration for Business Websites

🔄 Updated 1h ago
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Key points

  • Self-hosted RAG chatbot platform for business websites.
  • Uses websites and PDFs as knowledge sources for grounded answers.
  • Supports OpenAI, OpenRouter, Groq, Ollama, and vLLM providers.
  • Encrypts API keys and stores data locally with SQLite.
  • Provides a 2-line JavaScript snippet for website embedding.

Self-Hosted Chatbot Platform

Bolnee-Chat is a newly released self-hosted RAG (Retrieval Augmented Generation) chatbot platform designed for business website integration. The platform allows users to deploy and manage chatbots on their own infrastructure, offering control over data and operations.

Knowledge Integration and LLM Support

The system enables chatbots to answer questions based on specific knowledge sources, including website content and uploaded PDF documents. It supports integration with various OpenAI-compatible large language model (LLM) providers such as OpenAI, OpenRouter, Groq, Ollama, and vLLM, allowing users to choose their preferred model.

Technical Features and Deployment

Bolnee-Chat stores all data, including visitor chats and knowledge chunks, in a local SQLite database. Provider API keys are encrypted using AES-256-GCM. Integration into a website is achieved by embedding a two-line JavaScript snippet. The platform also includes features like knowledge management, avatar file storage, and a dark-mode console for administration.

Installation and Configuration

Installation involves cloning the GitHub repository, configuring environment variables, and running npm commands for setup. Users can add knowledge sources by providing website URLs or uploading documents like PDFs, TXT, MD, DOCX, or FAQ files. Chatbot configuration includes selecting an LLM provider and model, with encrypted key storage ensuring security.

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Reporting from

Bolnee-Chat is a new self-hosted RAG chatbot platform that allows businesses to integrate AI chatbots into their websites using their own infrastructure. It enables grounding answers in provided sources like websites and PDFs, and supports various OpenAI-compatible LLM providers.