{"name":"Article-Assistant--RAG-Telegram-Bot: AI-Powered Knowledge Base via Telegram","description":"The Article Assistant is a sophisticated RAG (Retrieval-Augmented Generation) Telegram bot designed to create interactive knowledge bases from various documents. Users can upload PDFs or provide URLs, and the bot will provide AI-powered answers with source citations. This tool efficiently transforms static content into a dynamic, queryable resource.","github":"https://github.com/Konstantin-vanov-hub/Article-Assistant--RAG-Telegram-Bot","url":"https://osrepos.com/repo/konstantin-vanov-hub-article-assistant--rag-telegram-bot","source":"osrepos.com","sourceDescription":"This repository profile is provided by osrepos.com, an open source repository discovery platform.","repositoryProfile":"https://osrepos.com/repo/konstantin-vanov-hub-article-assistant--rag-telegram-bot","generatedFor":"open source discovery and AI-assisted research","markdown":"https://osrepos.com/repo/konstantin-vanov-hub-article-assistant--rag-telegram-bot.md","json":"https://osrepos.com/repo/konstantin-vanov-hub-article-assistant--rag-telegram-bot.json","topics":["Python","Telegram Bot","RAG","AI Assistant","Knowledge Base","LangChain","OpenAI","Document Processing"],"keywords":["Python","Telegram Bot","RAG","AI Assistant","Knowledge Base","LangChain","OpenAI","Document Processing"],"stars":null,"summary":"The Article Assistant is a sophisticated RAG (Retrieval-Augmented Generation) Telegram bot designed to create interactive knowledge bases from various documents. Users can upload PDFs or provide URLs, and the bot will provide AI-powered answers with source citations. This tool efficiently transforms static content into a dynamic, queryable resource.","content":"## Introduction\n\nThe Article Assistant is a sophisticated RAG (Retrieval-Augmented Generation) Telegram bot that transforms articles and documents into interactive knowledge bases. This powerful tool allows users to upload PDFs, provide URLs, or even process YouTube videos, then ask AI-powered questions and receive answers with source citations. Built with Python, LangChain, and OpenAI, it offers a seamless way to interact with your content.\n\n## Installation\n\nGetting the Article Assistant up and running is straightforward, with a recommended Docker deployment for ease of use.\n\n### Docker Deployment (Recommended)\n\nFor the simplest setup, use Docker and Docker Compose:\n\nbash\n# Clone the repository\ngit clone https://github.com/KonstantinVanov/Article-Assistant--RAG-Telegram-Bot.git\ncd Article-Assistant--RAG-Telegram-Bot\n\n# Configure environment variables\ncp .env.example .env\n# Edit .env with your Telegram Bot Token and OpenAI API Key\n# nano .env\n\n# Build and start the containers\ndocker-compose up -d --build\n\n\n### Traditional Installation (Without Docker)\n\nIf you prefer a traditional setup:\n\nbash\ngit clone https://github.com/KonstantinVanov/Article-Assistant--RAG-Telegram-Bot\ncd Article-Assistant--RAG-Telegram-Bot\npython -m venv venv\nsource venv/bin/activate  # Linux/Mac\n# venv\\Scripts\\activate     # Windows\npip install -r requirements.txt\n\n\nAfter installation, create a `.env` file with your `TELEGRAM_TOKEN` and `OPENAI_API_KEY`, then launch the bot:\n\nbash\npython RAG_bot/bot_main.py\n\n\n## Examples\n\nThe Article Assistant offers a variety of interactive features:\n\n*   **Upload a PDF**: Send a PDF file directly to the bot for indexing.\n*   **Process YouTube Videos**: Provide a YouTube URL, and the bot will download, transcribe, and index the video content for Q&A.\n*   **Ask Questions**: Once content is indexed, simply type your questions to get AI-powered answers.\n*   **Get Summaries**: Use the \"Summary\" button to generate key point summaries of your indexed content.\n*   **Multilingual Support**: Switch between English and Russian interfaces using the language button.\n\n## Why Use It\n\nThe Article Assistant stands out as an invaluable tool for anyone looking to extract knowledge efficiently from various sources. Its key benefits include:\n\n*   **Interactive Knowledge Bases**: Transform static articles, documents, and videos into dynamic, queryable resources.\n*   **Source Citations**: Get accurate answers backed by direct references to the original content.\n*   **Versatile Content Support**: Process web articles, PDFs, TXT files, and even YouTube videos.\n*   **No Request Limits**: Enjoy unlimited questions and processing for your indexed content.\n*   **Easy Deployment**: With Docker support, getting started is quick and hassle-free.\n*   **AI-Powered Insights**: Leverage advanced RAG architecture for intelligent summarization and Q&A.\n\n## Links\n\n*   **GitHub Repository**: [https://github.com/KonstantinVanov/Article-Assistant--RAG-Telegram-Bot](https://github.com/KonstantinVanov/Article-Assistant--RAG-Telegram-Bot){:target=\"_blank\"}\n*   **Contact Developer**: [@Konstantin_vanov on Telegram](https://t.me/Konstantin_vanov){:target=\"_blank\"}","metrics":{"detailViews":1,"githubClicks":0},"dates":{"published":null,"modified":"2026-04-24T07:56:18.000Z"}}